Transcript

SUSAN AMARA: Thanks, Dan. And I also want to thank the panelists and previous speakers for providing such a compelling and exciting vision of the future. I think it’s given me a lot of optimism for the future. So, thank you all. I’m Susan Amara. And I’m the scientific director at NIMH.

And it’s really my honor and pleasure to introduce Dr. Kafui Dzirasa. Dr. Dzirasa is the A. Eugene and Marie Washington Presidential Distinguished Professor in the Departments of Psychiatry and Behavioral Sciences, Neurobiology, Biomedical Engineering, and Neurosurgery at Duke University. I had to have notes to remember [laughs] all that.

He received his M.D. and Ph.D. in neurobiology from Duke in 2009. And completed his residency in general psychiatry in 2016. Dr. Dzirasa really has been at the forefront in the development of state-of-the-art approaches aimed at revealing the circuits and brain states that underlie neurological and mental disorders.

Through elegant studies using in vivo electrophysiological recordings in animal models and together with machine learning approaches. His work has really explored the changes in the large-scale patterns of brain activity — brain network activity that can be linked to the presence or absence of depressive states.

His overarching goal is to combine his research, medical training, and community experience to improve outcomes for diverse communities suffering from neuropsychiatric disorders.

Among his many awards — and I really mean many — and honors, he’s received the Presidential Early Career Award for Scientists and Engineers. He’s also received the Society for Neuroscience Young Investigator Award.

And in 2021, he was elected to the National Academy of Medicine. Please, give a warm welcome to Dr. Dzirasa.

KAFUI DZIRASA: Well, good afternoon. It’s a tremendous pleasure to be here. In many ways, this is home for me. I grew up not too far down the street, in Silver Spring, Maryland. And spent a ton of weekends at the Air and Space Museum. So, this is like it right here [laughs].

I met the NIMH in 2009. I was in my last year of medical school and I wanted to figure out what translational research was. So, I signed up for an array rotation at the National Institute of Mental Health. And I was in the laboratory of Carlos Zarate.

And while I was there, I got to meet the director. I emailed him and said, “I’d love to talk to you about futures and, you know, where neuroscience is going.” And Tom took me out to lunch. And he played such a remarkable role in shaping much of what you’ll see today.

He convinced me to do psychiatry residency. I see a bunch of other friends here from Maryland. People I’ve met along the way who have really shaped how I think about research. And how to bring a bunch of different disciplines in my experiences to bear on how I think about treating mental illness.

I’ll warn you in advance, this talk is going to wind through a lot of different directions. My goal is to solve a massive problem. And I’m an engineer, which means I grab from all kinds of stuff to solve that problem. I’ll do my best to orient you to the different disciplines and spaces that we’ll move into as we go along.

All right. This is my status slide in here, but I’m working on it [laughs]. All right. So, this slide needs no background here, right? These illnesses impact people. Our whole country is totally familiar with them, particularly, as we’ve gone through the pandemic, the impact they have on individuals’ lives.

If you haven’t experienced these in a deep way, you see them in your kids, your family members, your loved ones. When we look at our young people, they’re suffering tremendously. These sorts of plots on — this is particularly looking at persistent feelings of sadness in our young people. These sorts of plots are alike all throughout the world.

And so, these illnesses are impacting people tremendously. Now, as Brittany talked about during her talk, I think this mental health model of preventing illness is something that’s central to how we should be thinking about things. And [unintelligible] sort of that triangle outlined that way.

I didn’t get an M.P.H. [laughs] in my many years of school. But I love this idea of prevention. And I got obsessed with it as an early career faculty member as well. Can we actually prevent mental illness? And there’s sort of two things that I anchored the idea of preventing mental illness around. The first one is, can we predict who’s going to get sick, right?

So, we need some sort of prediction mechanism. And then we need some sort of intervention, right? So, the talk is going to center on this idea of risk prevention or prediction and intervention.

All right. I hit this concept when I was in residency at Duke, how it was my chair at the time. And I had this observation that folks kept coming into the inpatient hospital. And there was this precipitating factor that showed up whether you had depression or bipolar disorder or schizophrenia, there was like stress, right?

And so, stress seemed to be there at the onset of illness, whether it was you sending your teenage — emerging adults off to college. Or whether you’re having some major family trauma. And again, we all get this as we’ve gone through the pandemic. So, stress was this major participating — precipitating factor.

But not everyone who experienced stress has a major psychiatric illness, right? And so, what I really became interested in were, what were the biological factors that determined who, when they were stressed, would ultimately decompensate or have illness?

You see that the red squares there. And who would ultimately not develop illness? And we’ll call that resilience through the top, right? And so, our idea was basically to track individuals. And those individuals not being humans. I’ll get there in a second.

And see if there was a central biology that mediated vulnerability. So, vulnerability means not being resilient to future stress. And we’re able to do this. We published that work in 2018. But we were able to find a biological signature — in other words, a biomarker associated with vulnerability to future stress.

So, I’m going to show you how we did that now. We’re going to sort of force into neuroscience and then into machine learning. So, we record electrical activity from many sites in the brain at the same time in mice. That’s our model organism that we use.

And you’ve seen brain waves like this. You’ve seen them throughout the day. Antonio showed some slides with brain wave. Nicole showed some slides with brain wave. We’re recording electrical activity from the tips of individual wires inside the animal’s brain.

And then we can do standard engineering analysis. We can ask how much activity is there in that wave of electrical activity. These waves represent populations of neurons firing together. We can look at activity across different frequencies, which — in each of those brain areas.

And then we can take advantage of engineering principles that say, “Things that change together over time tend to lie within the same system.” So, we can quantify how much these brain rhythms in different brain areas change together over time.

And you’ll hear me use the term synchrony or coherence, right? I’m just showing you two brainwaves here. And you can see how the red tends to align the peaks together, right? So, that’s synchrony.

Then we can borrow from our friends. This is used in weather forecasting or in the stock market. It’s essentially statistical forecasting. And what you can do is actually infer how information is moving through the system.

So, if the current activity in one brain area, let’s say hippocampus, aligns with future activity in prefrontal cortex. In this case, you can infer that information is moving from hippocampus to prefrontal cortex. So, that’s directionality. Or you can do the same thing and calculate that information in the other direction and infer that information is moving in the other direction.

So, for each mouse, we’re recording about 10,000 data points per second, right? We’ve got activity in each of the brain areas. We’ve got activity across frequencies [laughs]. And then we’ve got these frequencies interacting with each other, basically creating a really big data problem.

And so, we started acquiring this information, and then we actually didn’t know how to make sense of it. And so, one day, I found myself talking with a colleague. He was the chair of computer science and electrical engineering. And his graduate student at the time, now — who’s now a tenured faculty member at Duke, about this challenge of how you make sense of all this data.

And they were working across multiple disciplines, including like weather forecasting. And they said, “The problem you have in neuroscience sounds a lot like the problems we have in geothermal imaging.” And so, they took their models. They built this model out, which was to make sense of our brain information that we were gathering.

And I’ll explain to you what you see here through an analogy, right? So, when you hear music, right, you’re basically hearing pressure waves traveling through the air, about 10,000 oscillations per second.

So, think of your LFPs as music, right? So, brain music — you’re hearing music. And what we’re going to do is we’re going to take that music and then we’re going to chunk it up into notes, right? And those notes are going to be the oscillatory amplitude measures of power that I showed you, the synchronization or the leading and the lagging.

So, we’ve got all this music. We’re going to break it up to notes. Makes sense? And then we’re going to ask how those notes change together over time. In other words, we’re going to figure out the chords that are playing and the instruments that are playing through a process called, using machine learning, a supervised auto-encoder.

And then we’re going to relate those chords to behavior. So, what the animal’s doing, right? And we’re going to build one final piece onto this model that I think is the most important piece. We’re going to ensure generalization.

And what that means is when we learn a network, we’re going to make sure that that works more than just for the network, the animal that we’ve learned it on, right? And the principle here that you can appreciate when you’re a clinician is if you have any sort of measure, like an EKG, when you go in the emergency room, you want to make sure that it works for the new person that comes in the door. Not just everybody that came in the door before.

So, we’re going to build on this piece that makes sure if you hear that music with a new tempo or a new set of instruments, you still know it’s the same music, right? So, we’re going to ensure that it generalizes.

Okay. So, here’s a paradigm that we’re going to do this in. We’re going to take a bunch of C57 mice. This is an inbred strain of mice. And then we’re going to implant them with electrodes across a series of brain areas that have been implicated in stress behavior.

So, for the neuroscientists here, infralimbic and prelimbic cortex, nucleus accumbens, ventral hippocampus, amygdala, and ventral tegmental area. Everyone else ignored those words [laughs]. And we’re going to record brain activity.

And then we’re going to take these mice and we’re going to put them through a stress paradigm. And the way the stress paradigm works is we put them in the same cage arena with an animal that’s about 50 percent bigger. And these are going to be retired males, which makes them really aggressive.

And then we’re going to pick the 10 percent most aggressive of these aggressive mice, right? So, if anyone has an older sibling, it was just like that growing up. So, this doesn’t go well for the little mouse. It gets beat up.

And then after 24 hours, you put it in a new cage with a new older sibling who also beats it up. So, it gets 10 days of this in a row, getting beat up by different mice. This work was published, led by Rainbo Hultman, who’s now in a faculty at Iowa.

All right. And what’s fascinating about this is if you take these genetically identical animals and you put them through this paradigm, about 40 percent of them look just fine — mostly fine. Sixty percent of them don’t sleep well. They don’t like rewarding substances. They don’t like other mice. So, they have the stress-related behavioral problems, right?

So, now you’ve got the groups that we set up in this sort of prevention algorithm. We’ve got everybody before stress. We stress them out. We know how they respond to stress. And so, we can look at their brain activity before stress.

When we do that, we see something that looks like this. And we call these our electrical functional connect domes. I’ll tell you the take home before I explain these. The take home is the picture on the right is different than the picture on the left, right?

[laughter]

All right. So, the picture on the right is the signature that shows up in the animals’ brains after their stress. And the signature on the left is a signature that is there before stress when all the animals otherwise look exactly the same, right?

So, you’re looking around the rim of the circle, we’ve got our brain areas there. If you see color around the tire, it means that brain area in that frequency contributes to the chord. It’s part of the chord that’s playing. The lines through the center means a brain area synchronizing.

And for the brain areas that are synchronizing, you see the information moving through the brain at the bottom. But again, the take home is, there’s a signature that is different that predicts who’s going to respond well to stress and who’s not. So, we achieved the first part.

So, we’re like, you know, nine minutes into the talk, [laughs] and prediction is done. Which means intervention is going to turn out to be way more complicated than we anticipated. This is the fun of science.

All right. So, we love using simple assays in the lab. The former director is probably cringing right now. He is saying, “This is not depression. This is not depression. I’m going to say it.”

But we love using these simple tests. One, because there’s a ton of literature running and other people have used it. And I’m not arguing that this is depression. I just need you to accept two things so we [laughs] — before we move on.

The first is that this is stressful for the animal, right? I can objectively tell you this is stressful because we’re going to measure the [laughs] animal’s stress hormones and it goes up when we do this to the animal, right? So, we just need you to accept that this is objectively stressful.

The second thing is that this assay is sensitive to how much stress the animal has previously been exposed to. So, if I stress an animal out and then I put it on this test, it behaves differently, right?

So, the test is stressful and the assay is sensitive to prior stress. That’s it. It’s not depression. Not depression. All right [laughs]. So, we’re going to take advantage of these two things by putting the animal on the test two days in a row, right?

And so, it’s in the same context. But the difference between the first day and the second day is it’s been previously stressed, which is the stressor of the first day. And what we’re going to ask is, how do computations in the animal’s brain change as a result of the prior stressor, right?

So, is it computing different between day one and day two? All right. And when you do this again to a group of animals — I’m showing you a bunch of animals here. I’m showing you their behavior on the first day and the second day.

As a population, the animals show greater immobility on the second day. That’s what I mean when I say sensitive to this — the prior stress. But it’s not all the animals. There’s some variability across the population of animals.

Okay. So, we’ve got our animals implanted. We’re recording from a series of brain areas. And what we want to know is, do any of the computations in any of the brain areas change? It’s sort of a brain screen of what’s changing as a result of prior stress exposure that computes how you deal with stress.

So, recording all these brain areas, we’ve got day one in gray, day two in red. I’m showing you a bunch of single cells that we’ve recorded. And the thing to take home from here is there are two brain areas that the computation looks a lot different, right?

One is infralimbic cortex, which is in the mouse, what we call mouse prefrontal cortex. And one is in the medial dorsal thalamus. So, the computations in the other brain areas look fine. But these two areas have changed.

Again, we’re not recording comprehensively all the brain areas. But it’s highlighting that something interesting might be going on here. So, now, we’re going to look at each individual mouse, right? We are recording before — we’re pulling a bunch of cells.

Now, we’re going back to the oscillations. And the oscillations, we get an oscillation from every single mouse, right? So, we’re going to ask the simple questions; are — is the power in these brain areas different? Right? Prefrontal cortex, infralimbic cortex, or medial dorsal thalamus? The answer is no.

Is there synchrony between them? No [laughs]. Is the flow of information different? No. This is again — the rabbit hole gets deeper. And we were sort of reminded at the time that there was another interesting pattern of synchronization that could happen in the brain, right?

So, everybody’s thinking of things changing together. You can also have a pattern of synchronization where things are changing across frequency. So, it’s another pattern of synchronization. I practiced to get that right in talks [laughs].

So, it’s another way the brain can synchronize. And this is called cross frequency phase coupling, where you have the amplitude of the higher oscillation synchronized with the phase of the low oscillation.

So, we calculated this property. And I’m showing you a plaque here. The phase of infralimbic cortex is on the bottom. The amplitude of medial dorsal thalamus is on the y-axis. And red is the — is coupling. Blue is no coupling. So, we can actually find coupling between these two brain areas across frequencies.

And this coupling changes between day one and day two. And importantly enough, the amount that this coupling changes is related to the individual behavioral change of each of the animals. So, it looked like we found a signature that we can go after that’s involved in how the animals are adapting to stress.

Okay. So, I’m an engineer. So, I immediately think of, you know, two things, right? Whenever we observe something, it could be the thing, right? So, this is the thing causing our stress problem, right? And what we want to do then is prevent it, right?

So, it’s a primary problem. And if it’s a primary problem, we want to get rid of it. The issue is, it may be compensatory, right? And what I mean by compensatory is if you run up a flight of stairs, your heart rate starts going faster, right?

What you don’t want to do is stop your heart rate from [laughs] going faster. Because what it’s trying to do is get more blood to your muscles, right? So, the heart rate increase is compensatory.

So, we need to know whether it’s primary compensatory because it determines whether we want to create the signature or get rid of the signature, right? So, the way we’re going to do this is we need to figure out some way to create cross frequency coupling in the brain.

You heard some talk — Antonio mentioned this. And Nicole mentioned this as well, about closed-loop modulation, right? So, we’re essentially going to use the same tools they talked about to create closed-loop modulation. And what we’re going to do in principle is we’re going to read electrical activity from infralimbic cortex.

So, the slow away from the infralimbic cortex. And then we’re going to stimulate the medial dorsal thalamus at the higher frequency, essentially coupling them across frequencies. And we somehow got to figure out how to read the information and put it back in the brain in about 30 milliseconds.

I had a really awesome undergrad in the lab who figured out how to do this. And so, we’re just going to extract information from the mouse’s brain, process it in a computer, and figure out what the wave is in infralimbic cortex.

And then stimulate a high frequency burst in thalamus that’s timed to it. And we’re going to use a tool called channelrhodopsin. The simple sort of take home of channelrhodopsin is blue light makes cells fire [laughs], and yellow light doesn’t, right?

So, blue light’s going to be our experimental group. Yellow light’s going to be our control. And we’re going to create this within the animal’s head and see what happens. When we did that, again, blue light’s our experimental group, yellow lights our negative control. I’m just showing you the amount of data mobility the animals show when we do this. When we basically play that signature, read from infralimbic [phonetic] cortex right into mediodorsal thalamus, it makes the mice less immobile.

In other words, it looks like we’re pushing some degree of resilience into the animal’s brain by doing this, right? And this argues that the signature isn’t actually primary. It is compensatory giving us a pathway to intervene now in specific animals. So, I’m just showing you what this looks like on the top here. In other words, when we time the signatures to the wave, the animals, green is good, right? It shows more behavior that looks like resilience.

But we did two important controls that really highlighted what we were running into. The first thing we did was we delivered the exact same number of light pulses into the brain, right? So, maybe this is just light going in the brain. This is just stimulation.

So, we delivered the exact same number of light pulses. We just delivered them in a fixed pattern where it wasn’t related to the oscillations. Now, it’s not timed and we were shocked. The animal’s behavior actually went in the exact opposite direction. In other words, they got worse. And so, this is — for an exam, this is like signal to noise for us. We’re just putting noise in the brain and canceling out how the circuit is normally computing.

And then we did one final control which is where we said maybe it’s the threes that are important and not, you know, the timing. So, we just had another experiment where we played threes, pattern of threes in the brain and the animal has no behavior change whatsoever. And the reason this is likely happening is some of the threes ended up at the bottom of the peak and some of the threes don’t. So, it all basically cancels itself out.

But what this really highlights is that if we’re going to intervene, it’s not that we just need to sort of find the area of the brain and stimulate it, we need to have approach where we can record or read and write in a closed-loop way that gets the timing right. The timing’s critical.

Okay. So, we’re really excited about this. This was somewhere around 2016. And we were like, “We solved all the world’s problems. We’re going to cure mental illness.” All we need to do is figure out how to create massive numbers of post-loop stimulation devices, deploy them across the world, make everybody resilient, and then we will retire and enjoy ourselves.

This is a picture of my family and the open chair is my uncle’s. And my family on the bottom row, four out of five of the siblings carries a major psychiatric diagnosis whether depression or bipolar disorder, schizoaffective disorder. And this is my grandmother’s funeral. The open chair is my uncle’s who’s — who has bipolar disorder and totally decompensated when his mom passed away.

And I used this picture because I had a conversation with him about a year and a half before as we come up with this beautiful closed-loop stimulation device. And my motivation for getting into science and getting into this area of work is entirely selfish. Like I want to help my loved ones. Everyone else will benefit as a process of this but I fear for my loved ones. And I just like to be upfront about that.

And I was talking to him and he was like, “This is wonderful. It’s amazing. The whole family is so proud of you. You’ve done it. Tell me more about how this is going to get to the third world because this isn’t God.” And I remember sitting there excited and then ashamed because there was no way it was going to get to the third world.

And in looking at those initial graphs that I put up, seeing the burden of illness worldwide with depression being a bit top of the list, it occurred to me that I was working on making interventions that was not going to move the needle on the burden of illness in the world at all because it just wasn’t going to get to enough people, right? It was going to take, you know, eight billion down to — let me not do the calculating, 7,999,999,999. In other words, it wasn’t going to move things enough. So, we needed to go back to the drawing board and think about how would one make a scalable intervention that could improve resilience.

All right. So, we started thinking — this is all conceptual, right? It’s a concept of a plan. And we started thinking about what is like a scalable intervention? So, it occurred to us like two things are for it to be scalable. Antibiotics and vaccines, and they could be deployed worldwide. My thoughts on vaccines changed a little bit after the pandemic but sure. Before then, I thought they can be deployed worldwide relatively quickly.

Now, antibiotics have an interesting thing. What they do is they target non-self, right, to make self, to protect self, right? So, that’s not what we’re trying to achieve with — in the case of mental illness. Vaccines on the other hand target self to make itself more resilient to the environment. So, in principle, the concept is what we will want to achieve is a vaccine, right? So, let’s see if we could turn this like brain stimulation device into a vaccine.

So, in 2018, I was on the BRAIN Initiative work group and I heard about like two exciting technologies being developed that made this concept a little more concrete. The first one was a human brain cell atlas that’s now underway. And the idea is we were going to sequence all of the cells in the human brain and find out the gene expression profiles, each individual cell type, and we’re going to do this across all ancestries so it’ll work for everybody. And what this would ultimately provide is a GPS system that you could use to express things in specific cell types. So, it’s a locator signal, right?

The second thing that was being created were delivery systems that would cross the blood brain barrier. There’s a colleague of mine at Caltech, Viviana, who’s working on AAVs that cross the blood brain barrier, right? If you could take these two technologies and combine them, you could create an AAV that you could deliver a package to specific brain cell types that you could package into a vaccine that could be scalable. And all you needed to do was take that closed-loop electrical stimulation system based in silicon and turn it into proteins. And so, the entire rest of this talk is going to be focused on our goal of turning our closed-loop device into proteins.

So, I’d spent time in medical school and as part of medical school, we rotate through a bunch of rotations. One of which is cardiology. And so, I’ve always been obsessed with the heart. And it turns out this heart has an interesting what we call [unintelligible] system that takes information. Ions from one cell and pass it directly to the next cell and it’s dumped through gap junctions which are called electrical synapses. You could use those terms interchangeably.

So, it passes ions from one cell to another, ions are electricity. So, it reads and writes from one cell to the next. That’s why your heart stays synchronized. These gap junctions are made of connexin proteins. They are expressed in most of the tissue throughout the body and 20 isoforms in humans. There are some challenges with them which is they’re bidirectional. You ever see a heart defibrillate, it’s like current moving in all kinds of directions. There are all kinds of things going on.

All right. What was interesting about gap junctions is about six or seven years earlier, somebody had taken these connexin proteins and put it in worms. They expressed them in neurons in worms. And what they showed you could do is just by expressing these proteins, you can create an electrical synapse or gap junction between them, synchronize these neurons, and it changes the behavior of the worm. So, you can essentially rewire or edit part of a circuit just by putting gap junctions in there.

Now, this is great in worms because worms have one cell of each cell type so your GPS system is like sort of really optimal. You can appreciate the challenges of trying to do this in a mammalian nervous system. Mostly because you have many cells of the same cell type. So, let’s suppose you wanted to have a closed-loop system that read from the presynaptic neuron on the left and wrote into the postsynaptic neuron on the right, you can insert gap junctions in between them that you see there in pink.

So, it’s sort of like an electrical synapsis that you put between them. But you would immediately have two problems. The first of which is you’d also express gap junctions on the other presynaptic neuron because it’s the same cell type. And what that would do, it would ultimately scramble the signal between the presynaptic neurons because current will be flowing in directions that it ultimately shouldn’t.

The second thing is because the gap junction is essentially poor, you’d have current moving in both directions. So, this is sort of like talking to somebody when they’re yelling at you. It’s not really useful.

And so, we had a concept of a plan and so we made a viral vector with gap junctions just to try this out to see what would happen. We put it in the ventral hippocampus in mice. I’m showing you two doses which we did this and we injected the mice. This is — my grad students said we really don’t have behavior. I said, this is the clearest behavior that I’ve ever seen. It was totally lethal. The animals had seizures and died. Because we were essentially hyperconnecting their hippocampus, exactly the picture that you would see on your left.

And so, we had a — what I call my dream team in science. It’s generally some really smart people. And here’s the idea that we came up with. Instead of having the gap junctions work like stickers, what if we made them work like magnets? Where there’s a positive end and a negative end. Excuse me for everyone — any one that’s color blind. The colors will have relevance later.

But the idea is the green, if it’s a positive event, it won’t interact with green. If red is negative, red won’t interact with red. But the green will interact with red. And just for kicks, let’s make it so current preferentially flows in one direction. So, this is conceptually what we’re trying to achieve.

So, I had a team of — I call this my dream team. They’re all — they were all undergrads at the time. Two of them have PhDs now. One’s a medical doctor. Just to show how long this has gone on. But I love using undergrads for projects because when you tell them stuff, they don’t know there’s no way it will work.

So, they searched through the literature. They searched through all kinds of connexins and all kinds of species. They searched for innexins which are invertebrates, pannexins, and came up with this pair that’s in goldfish and perch fish. And connexin 34.7 and 35, their names are based on how much they weigh in kilodaltons.

And what was really fascinating about this pair was this pair could come together, these two different proteins would come together to form a gap junction. They also conducted current at exactly the amount that we would want for the mammalian nervous system. And they had this cool property they tended to rectify. In other words, they sent current more in one direction than in the other. So, this is our baseline pair that we’re going to start with.

The issue with this pair is that while 34 and 35 will come together, 34 can also come together with itself and 35 can come together with itself. So, it does what we want but it also does things that we don’t want it to do. And so, at that time, I’ll be honest, I’m going to acknowledge this now, I barely passed biochemistry in medical school and cellular biology. But it was clear that we suddenly had to become biochemists and cellular biologists to figure out how to do protein engineering to make these cells, these proteins do what we wanted them to do.

So, it turns out that docking or the coming together between these connexin proteins, these halves, these hemichannels are controlled in part by extracellular loop 2. So, residues on extracellular loop 2. So, we just had the simple idea what if we could figure out which residues control the docking, mutate them, and then find a pair that does something that nature’s never created before. This was our idea that we put into our concept of a plan that we put into a BRAIN initiative grant. And believe it or not, they funded it.

So, here’s our strategy. A postdoc from my lab came up with this idea on how to achieve this. So, here’s a connexin life cycle that happens between two cells. So, you have two cells, cell on top, cell on bottom. The connexins are synthesized, trafficked to the circuit’s surface and then they combine to form a gap junction that you can see there on your right top left corner.

And when they do this, when you need to get rid of the gap junctions, you don’t actually rip it in half. One cell swallows the whole gap junction. And so, what you realize you could do was just tag the connexins with the green fluorescent protein or red fluorescent protein. So, one cell expresses red connexins and one cell expresses green connexins.

And then you know you formed the gap junction because you get green and red in the same cell when it swallows it. So, you’re simply asking question does a single cell have green and red in it. If it does, you form the connexin. So, I’m going to show you what this looks like. Pay attention to the upper left hand corner. I’m showing you a bunch of cells that we’re just doing live imaging. And you’ll see those sort of green and red little circles that show up. Really small green and red double layer circles that show up. That means that you formed a — you formed a gap junction.

So, here’s what we were able to do. We just take a connexin. We’ll take one of our mutant pairs that we’ve created. We created 70 of each one. We tagged one with green. We tagged one with red. We put them together. We let them hang out. And then we see if their cells with green and red in it using a technique called flow cytometry.

And all it’s going to do is tell me is whether individual cells have green and red in both of them. You see that on the bottom right hand corner. Pay attention to the plot all the way on the bottom right. One axis is how much green do you have. One axis is how much red do you have. Each dot is an individual cell. And you could see that there’s nothing really in the upper left hand — upper right hand corner. There’s only green on one axis and red on the other. So, those connexins proteins do not interact.

If you look at the other axis, the plot right on top of it, this is gap junctions are being formed. In other words, you have blue dots that are off the axis. They are all sort of filling out the center there. So, it’s a really simple quick assay that we could do when we have pairs to see if they form a gap junction. So, here’s what we’re going to do. We’re going to mutate a bunch of proteins. We’re going to test them against ourselves. And we’re looking for proteins that don’t interact with themselves. We don’t care why it doesn’t interact with itself. We don’t care if the protein never gets formed or it doesn’t corrupt. We just want to make sure it doesn’t interact with itself. So, that’s step one.

Then we’re going to take all the proteins that don’t interact with themselves and we’re going to see if it interacts with the other protein. If it does interact with the other protein, it means it’s getting formed correctly. And then because for kicks, we’re not interested in curing mouse depression. We’re going to test this against all of the other human connexin proteins just to make sure we have a translational path for it.

Okay. And you can see on the bottom right, basically 0.2 percent. So, none of the cells really have both. Here, 17 percent of the cells have both when it’s positive. So, we go through this process and again, here’s our three steps. We’re going to test them against themselves. We’re going to test them against the other one. And then we’re going to screen them against human connexin proteins particularly those in the brain but we ultimately did all of them to make sure it doesn’t do that.

When we do that, with 15 proteins make it past around when they’re screening. So, we started with 150. We ended up with 15. We screen them against each other. We’re really excited. We ended up with three pairs. These three pairs, the halves don’t dock with themselves but they dock with the other one so it’s a really cool property that hasn’t been seen before in nature.

And then we took the last step. Again, because selfishly, my goal is to help my loved ones so we want this to work with humans. And none of the pairs survived interacting with human connexin proteins. So, they all interacted with other human connexin proteins. So, we had what may have been a reasonable mouse tool but not a useful translational tool in the long run.

And so, we felt good but progress was sort of stifled. And then it got really bad. This was all in March of 2020. And the lab shut down. And at that point in time, we took — we all took totally new career directions. We were all sort of making bread and cookies, playing around with yeast. And I just had a new graduate student join my lab who’s — he finished up at Berkeley a little earlier and he’s back on his computer science. And he convinced us to get him a supercomputer that he would put in his house. And — because what else are we going to do when the world shuts down.

And he started doing protein modeling. And so, he took all of the protein sequences, all the means that we created. Stuck it in the computer. Figured out how to build them into an artificial membrane and then calculate how these connexin proteins were interacting with each other. Basically, running through all of these pairs and seeing what their patterns of interactions were and what controlled them.

And not to soon after that, he sort of found this interesting code and determined how connexin proteins interacted with each other and docked. They’re sort of four residues with a second one down interacted with the three residues on the other side. So, it’s sort of this mechanism where the whole thing locked together. And so, what we realized we could do from this computational model was mutate the residues at select sites and create versions of the protein that only docked with each other. Not with themselves and didn’t interact or dock with human connexin proteins.

And so, we created these in the computer. Eventually, the lab opened up again and then we made these proteins in the lab. So, some of them we had real proteins that did this. All right. We quickly tested them just to make sure that they were functional. So, we put them in oocytes. These are basically frog eggs that had been used, sort of things that had been used classically in neuroscience. We put them in the oocytes, one in each one and then you see if electricity moves back and forth between them.

On the top, I’m showing you the wild type pair. On the bottom, I’m showing you the mutant pair. The take home here is there is current moving thorough those connexin proteins. So, check one.

Okay. So, then we went back to the C. Elegans and we loved the C. Elegans. Reached out to my colleague, Daniel Colon-Ramos, who is at Yale. I see Yale represented here. And who had been doing really cool work in C. elegans. And the C. elegans is a really nice system for testing out these connexin proteins. I’ll sort of orient you as I go throughout. I never worked with C. elegans before, so all of this is like really new stuff trying to solve a problem for me.

But C. elegans is nice because when it’s clear, and you’ll see why it’s really useful, that it’s translucent. It has 302, exactly 302 neurons and neuroscientists have done an amazing job of mapping behavior onto those specific neurons. So, they know what those neurons do. And so, it’s a really nice system to test out if we could change how neurons are interacting with each other because C. elegans also don’t have connexin proteins. So, it’s a nice clean system to test our proteins out.

So, here’s our assay that I’ll orient you to. So, C. elegans, I say, are a lot like graduate students. Whatever you feed them, they will return. So, if you feed a C. elegans at cold temperatures, it migrates towards cold temperatures the next day. If you feed it warm temperatures, it migrates towards warm temperatures. And that behavior in part is controlled by the interaction between two neurons. One called AFD, which is a sensory neuron. It senses temperature. And then one called AIY, which is an interneuron.

When you feed the C. elegans at cold temperatures, you can sort of see the — see where it says calcium rises. Look under that. I don’t have a laser pointer. Do I have a laser pointer? All right. So, you could see as the temperature rises on the plot middle on the bottom, the activity goes up. This is different at 61 animals and that’s just showing you how much activity you have in each of the cells. In other words, the cells fire more as the temperature goes up because it’s a sensory neuron.

On the right, you see what happens with the postsynaptic neuron when the connection between them is weak. Temperature goes up, that the neuron doesn’t respond. That’s when you feed the animals cold. When you give them a chance to go to find food, they go towards the cold. Makes sense?

All right. If you feed the animals at warm, that connection between the two neurons becomes much stronger. All right. And now, you can see that when you rise the temperature, the second neuron also increases activity because the connection between them is strong. And then the animals migrate towards the warm when you give them a chance to eat food.

So, you can assay how strongly are those two neurons connected by — if the animal floor is warm and there’s a calcium rise in the second cell. So, what we’re going to do experimentally is we’re going to take our proteins and we’re going to put them in the two cells. In case number one, we’re going to take the lock and put it in both cells. In case number two, we’re going to put the key in both cells. In case number three, we’re going to put the lock in one and the key in the other.

So, here’s what it looks like when you have the lock and the lock. This is the calcium imaging. In other words, when you look on the right, the lock and the lock, 34.7M1 and the key and the key, 35, 35. There’s no postsynaptic calcium rise. In other words, the connection between those two cells is weak as temperature goes up. It’s exactly what you would expect. The lock and the lock and the key and the key aren’t doing anything.

But when you put the lock and the key in, suddenly, that neuron starts behaving really different. Now, with the lock and the key in it, it’s as if you’ve edited or changed the connection between those two cells and you have the postsynaptic calcium rise. So, you’ve change how that cell is functioning. But the question is what’s going on behaviorally.

All right. So, the wild type cases are normal C. elegans. They like the cold. All these are cold trained. We put the lock and the lock in. The animals go to the cold. The key and the key, the animals go to the cold. But when you put the lock and the key in, suddenly, the behavior of the animals changes and the animals immediately prefer the warm temperature.

So, you can change the physiology and behavior of the animal by inserting or editing the circuit between them. Okay. And we also tested this against the connexin proteins in the human brain. They do not interact with our proteins. So, again, we’re just — at every step, we’re trying to make sure that we have a translational pathway.

Okay. So, what kind of stuff can we do with this? All right. So, we got really excited and we’re like, “Well, let’s go back to the beginning and see what happens with these little puppies and mice.” So, back to the beginning. We have this two-day assay that we’re going to subject our animals to. And when we recorded the animals in this assay, we found two brain areas that were important and the interaction between them, infralimbic cortex and medial dorsal thalamus.

And so, we took our viruses and we basically put them in infralimbic cortex and medial dorsal thalamus. We put the lock in the infralimbic cortex. Sort of waited it for it to express along the axons going to the medial dorsal thalamus. We put the key into the medial dorsal thalamus. Again, you could see the red and the green. We could see that we could get sort of these colors coming together in the medial dorsal thalamus. We went through and did some physiological assessments of this circuit and we showed that we could strengthen the physiological interactions between these areas. And then we wanted to know what would happen to the behavior of this animal.

So, again, as I showed you, if you put an animal through the two-day task normally, the exposure to the stress causes their behavior to change and they are more sort of immobile on the second day as a result of the exposure to stress. So, this is what happens when we put the lock and the lock or the key and the key in. They are sort of — they have circles or X’s there. The populations basically overlap and are pooled together there. And animals show increased –f they show adaptation to the stress. So, they are changing in the way that unedited animals are.

But when we put the lock and the key in the circuit, suddenly, we saw that the population of animals weren’t changing. We repeated this a few times. We’ve actually looked across a bunch of different assays at this point in time. But we are changing the physiology and the behavior of this circuit. So, for us, we were really excited about this because we sort of started with our huge closed-loop pacemakers, left the country, went to Ghana, went through a pandemic, came back. All sort of trying to come up with something that would help us find a scalable approach to improving resilience to mental illness.

All right. So, I’m here with one of my favorite slides in the world. I saw this at BRAIN camp. Tom invited me at the time. I was — last year, I was a PhD student to meet a bunch of leading and eminent neuroscientists in [inaudible] put this up as a mouse researcher. So, I was hurt by this slide. I will say that people show their facial expressions in rodents are predictive since that beautiful paper a few years ago by Nadia.

But this is a real problem. Because as you think about the work we’re doing in mice, whether it’s guilt, or suicidality, or sadness, we don’t have great ways of measuring that in these preclinical model organisms. And, in fact, if any of us were to see a mouse or a rat run across the room, most of us will jump on our chair or run out the room. Because — we might even call an exterminator. Because we’re not entirely convinced deep down inside that mice have feelings. It’s unclear if they pass the Turing [phonetic] test. We surveyed the American population. It’s unclear if they were — believe that they passed the Turing test.

I’ll ask a question. Right hands up. How many of you have a dog? Okay. Left hand up if you believe your dog has feelings. Yeah. Right. I gave a talk at a vet school and I was immediately convinced. Frankly, I’ve never had a dog. But I was convinced that dogs passed the Turing test, right? So, if at its core, psychiatric illness is so sure of occupational dysfunction that could cause all the illnesses, it’s a common thing. It occurred to me that dogs are sort of the only species that live, and socialize, and work with us the way we live, and socialize, and work with each other.

So, they both pass the Turing test and they embedded themselves within the structure that is disrupted in psychiatric illness. And so, someone asked me and said, “Could you do this work in dogs? Wouldn’t that be cool?” I said, “Absolutely not. There’s no way I would go anywhere near that.” And the person said, “No, you don’t understand. You’re giving your mice fluoxetine. We give dogs fluoxetine.” I never knew the dogs got Prozac. Dogs get Prozac, believe it or not. Because they have behavioral disorders that look a lot like the behavioral disorders that we have in humans.

And anybody who bought a dog during the pandemic and then went back to work suddenly saw their dog had separation anxiety. Just like your kids when you’re leaving them at kindergarten the first day. They look exactly the same. And I came across this fact that really changed the way I thought about this. And I was talking to a bunch of vets and there are all these sort of mixed breed pit bulls in Raleigh.

And they get anxious and when they get anxious, they get aggressive. And when they get aggressive, they get euthanized. Because in dogs, it turns out, anxiety and aggression could be terminal. And so, the case that this person, this vet that I was talking to made was that if you could figure out how to do this, you’d actually be saving dog’s lives.

So, I got really motivated around this question. How could we use neuroscience and cutting-edge neuroscience, as I sort of think about the future and the opportunities to help dogs. Not simply because it’s like probably a really good translational approach to understand human neuropsychiatric illness and how encoding happens and get to an endpoint. But also, because it’s just really valuable and useful to help dogs.

And people in America care about dogs. So, it took about two or three years to build out my first team of collaborators to take on something like this. And I was able to ultimately bring in the humane society as collaborator to figure out how we can ask questions. Like if we can understand aggression in dogs, could we use neuroscience to minimize it so that they get adopted from shelters.

And how can we understand pain in dogs in a way that decrease osteoarthritis? How can we understand social behavior in a way that help dogs live in our homes better? And in doing so, could we understand neuroscience in a way that gets us closer to ultimately develop therapeutics and interventions that help people like my family members.

So, I’m extremely grateful to be here and with — I’ll take this last two-minute privilege just to say this. Because I think it’s a real statement about American science. So, I want to talk about the people who do this work.

Liz Ransey was a postdoc in the lab who tagged the connexin protein with the different colors. She’s a first — she was a first-generation college student and she’s now on faculty at Carnegie Mellon. Ryan was one of those really amazing Montessori kids from San Francisco. Came to my lab as an undergrad. He was on the dream team. Did the master’s at Carnegie Mellon.

Dalton Hughes was a Meyerhoff scholar in Baltimore, Maryland. I met him as an undergrad. He’s now finished his MD PhD. Elise Adamson was an undergrad in Biomedical Engineering, came to my lab later. Did her PhD in Biomedical Engineering and is now consulting. Daniel Colon-Ramos who grew up in Puerto Rico is on faculty at Yale, my collaborator on the work with C. elegans.

Tatiana Rodriguez, in the upper left-hand corner grew up in the Appalachian Mountains in Maryland, is now doing her PhD in Toxicology at NYU. Catherine, who’s right below her was — grew up in Iowa. Had two kids during the pandemic. I literally saw her in lab the morning before she gave birth. And a week and a half later, she’s zooming in the lab. And I was like, “Please don’t do that.” But it really highlighted for me the importance of taking care of young people and young families and giving them good supportive childhood care. Because they play an important role in the discoveries that we make.

Steve joined my lab after finishing up his PhD at University of Pennsylvania. It’s been fantastic with his expertise in addiction research. Eli who’s now an MD PhD student in Oregon. Hannah Schwennesen who’s on the undergrad dream team is now a medical doctor finishing up residency in internal medicine.

Gwenaelle Thomas who was an undergrad at UMBC as well joined my lab, who experienced countless members in inner city New York who were murdered while she was growing up. And really had deep insights about how that impacts a person going through science. She became the second black female to get a PhD in neuroscience from Duke. In the middle, Nenad Bursac, who migrated here from Serbia. Next to him, the whiz kid from Berkeley whose family migrated here from Russia.

And then finally, in the bottom right-hand corner is Rainbow who migrated to my lab from Iowa. And Rainbow’s story is one of the most unique ones. Some of you know her. In graduate school, she started suffering from debilitating migraines and couldn’t look at the computer.

She joined my lab as a postdoc because she wasn’t sure that there were places in science for people who had disabilities and challenges. She ultimately finished her PhD. She’s now on faculty at Iowa and she won the NIH New Innovator award to study the neural mechanisms underlying migraines.

So, I think it’s a real statement on American science in how we create spaces for everyone to bring their disabilities and perspectives in. We can bring things and ultimately have a potential for helping people throughout the world. So, thank you so much for having me here.

Almost all of this was supported by NIMH. So, I want to thank you all. I met Josh at Society for Neuroscience in 2007. We’re sort of the only two really talking about brain oscillations in mice and how you might be able to decode emotions and behavior from them. So, this is home for me. Thanks.

FEMALE SPEAKER: That was fantastic. I have many questions but I’m just going to ask one. Can you talk more — so, okay. I love the idea of hacking into the biology and figuring out ways that we can change electrical activity in the brain.

But I want to know how much you understand how that electrical activity is actually tied to the computations that lead to the behaviors. Because we have been talking all day about how complex behavior is, how complex mental disorders are. So, what are your thoughts on what we need to do to figure that out or should we or can we?

KAFUI DZIRASA: Yeah. I have a concept of a plan. I don’t know. We have to test these things out empirically. I’m not by any means arguing that human beings go playing around with their connexin proteins tomorrow. I honestly haven’t figured out what resilience is. It may be that these animals are resilient to some things and not resilient in others or vulnerable to some things and not vulnerable to others.

So, I think we do have to learn that as what making an animal sort of more resilient to one stressor, we’re sort of creating problems in another domain. So, we have to learn all of that. The idea of getting upstream is to figure out what is common or sort of one convergent place that we can target to ameliorate the likelihood that many different psychiatric disorders would emerge rather than thinking about how do we get rid of hallucinations, how do we get rid of sadness moving forward or upstream for that.

But in the words of the great Desmond Tutu, don’t let him jump in the water.

FEMALE SPEAKER: And if I can just follow up that. In the way that you’re conceptualizing things and thinking about moving upstream, you really highlighted the importance of stress. And stress as being a driver, and trigger, and exacerbator of a number of different sorts. So, do you think you want to focus on understanding the mechanisms of — that explain how this neural activity leads to stress resilience or can we bypass that in a way and then still leverage these techniques?

KAFUI DZIRASA: It’s a great question. You’re sort of scratching on my multiple areas of training. So, I’m an engineer by origin. All right. So, my immediate gestalt is to say, “I just want to fix it. And if I can make it better and my family members aren’t suffering, I am okay and somebody else can figure it out,” right? So, it’s me gathering as much information as possible that’s necessary to solve the problem.

At the same time, I’m certainly a neuroscientist who’s curious and is taking a lot of tools and terms to understand things. But it’s understanding to a degree that I need to solve the problem and hopefully in the process, training some graduate students who will figure the rest out. If I could figure out how to modify neural circuits in a way they increase resilience and prevent the emergency psychiatric illness, I would be equally satisfied as the folks who created Prozac, and Haldol, and all of the other things that we still don’t understand exactly how they work.

FEMALE SPEAKER: Thank you.

FEMALE SPEAKER: Okay. We just have one comment from the participants online from Lauren Hill at NIMH. “That was awesome.”

KAFUI DZIRASA: Hello, Lauren. I actually thought it was a different Lauren Hill one. But we love you too, Lauren. [laughs]

FEMALE SPEAKER: Do we have more time?

KAFUI DZIRASA: Yeah.

FEMALE SPEAKER: Thank you for that fantastic talk. Such a fun one to end this long and interesting day. So, my question is coming from a clinical psychology background, interested in mechanisms, how specific or general do you think this mechanism is? I have two levels of that question so on the one hand, how important is it that your assay is the same day one and day two? And secondarily, what other kinds — you mentioned other assays. Like a swim test. I’m never good at — that’s my question. Thank you.

KAFUI DZIRASA: Yep. No, that’s exactly right. What our strategy has been is now, can we put animals through a bunch of different stress paradigms and with the same circuit beacon [inaudible]. Yeah. Let me just say this because I see Brianna sitting up there and I was super proud giving a talk. So, I met her when I went to the postdocs at Stanford and they invited me to give a talk. And I went out there.

And I’ll never forget her pulling me aside, “I’ve never met a Black faculty member.” So, for me, I have incredible sense of pride seeing her as a faculty member and all that she’s done to create space for other people. So, I wanted to just give her a special shout out. And I thank you all for having me here. It’s been a tremendous honor and a pleasure.

SHELLI AVENEVOLI: Wow. It’s been an incredible day on so many levels. I can honestly say I’ve learned something new from every talk I heard today. And I know it’s going to shape the way all of us in this room and those online think about the kind of science we’ve talked about.

So, first and foremost, thank you so much for being here. We know you’re incredibly busy people. But thanks for sharing the day with us. Traveling here, sharing the day, sharing your ideas, and letting us push you a little further. I acknowledge that the talks we asked you to give are much different than the talks that you would traditionally give. So, we appreciate that and acknowledge that.

It’s also my privilege to thank so many other people who were making — involved in making this day possible. I especially want to acknowledge Megan Kinnane sitting in the front row. Megan led the work group that really put together the agenda for today, the organization, and the implementation. And with her is Phyllis Ampofo up in the back. Syed Rizvi, Syed Rizvi and Nichole Cook are also in the back. And Elizabeth Sekine who is sitting up here next to Megan. Thank you all so much.

I also want to acknowledge that it takes a village to plan our 75th anniversary year celebration. And these are the people. We had three major symposium but we also had several different events throughout the year. We also have an amazing team that put together materials online. I do hope you check out our 75th anniversary website. It’s not going to stay there forever. But please check it out. We have videos. We have podcasts. We have feature stories. And I want to thank Natalie Zeigler, call her out especially for leading that aspect, creating the materials for us.

And lastly, I just want to thank members of the entire NIMH community which includes our investigators, our patients and families who contributed, our advocates and professional organizations that support everything we do. The celebration is really about all of us. So, we should give all ourselves a round of applause. And thank you for coming and enjoy the — I think we can stay here until 5:30 p.m. We have to be out by 5:30 p.m. So, enjoy yourselves and thank you again.

Transcript

DANIEL HANDWERKER: Good afternoon and welcome back from your break. My name is Dan Handwerker, and I’m a staff scientist in the section on functional imaging methods in NIMH’s Intramural Research Program. And it is my pleasure to introduce our next group of speakers.

Jahn Jaramillo is a doctoral candidate in the Division of Preventative Science and Community Health at the University of Miami. His research is centered on the health of sexual and gender minorities with a particular focus on integrating identity and cultural considerations into health promotion and HIV prevention strategies.

He is also dedicated to developing and testing HIV interventions that provide medically appropriate and culturally-competent care to Latina communities in South Florida.

Alexandra — Alessandra Angelino, who’s going to be participating remotely, is a pediatrician and fellow in the Department of Adolescent Medicine at the Johns Hopkins Center for Indigenous Health.

Dr. Angelino earned a medical degree from the Robert Wood Johnson Medical School and an M.P.H from the University of Washington. And she completed a pediatric residency training program at the University of North Carolina Chapel Hill.

Her research has focused on the health of Indigenous children and adolescents, including work relating to sexual violence and trafficking in Indigenous communities.

Dr. Brittany Rudd is an assistant professor in the Departments of Psychiatry, Psychology, and Law at the University of Illinois Chicago. Dr. Rudd completed her doctoral training in clinical science at Indiana University and postdoctoral training in implementation science at the University of Pennsylvania.

The central theme of her research is to accelerate research-to-practice implementation in settings that support young people who are marginalized due to race, socioeconomic status, and other factors. She’s especially focused on efforts to transform the current legal system into one that enacts an equitable justice and promotes mental health.

Dr. Oladunni Oluwoye is an associate professor in the Department of Community and Behavioral Health at Washington State University. She received a master’s degree in clinical psychology from Alabama A&M University and her Ph.D. in health promotion and education from the University of Cincinnati.

She is a health services and disparities researcher that utilizes culturally- and community-informed approaches to address inequities in mental health care. Please welcome to the stage, Jahn Jaramillo.

JAHN JARAMILLO: Hello, everyone. Muy buenas tardes. My title for today’s talk is called “Advancing Mental Health for All: Future Directions for Healthier Tomorrow and LGBTQ+ and Latinx Communities.”

I wanted to start off by giving a big thank you to the event organizers at the NIH for planning this event and for extending an invitation for me to be here today at the biggest stage yet for me as an emerging scholar, scientist, dreamer, and leader in the field of HIV and public health. I never thought my journey to help my community would take me here in front of you, of esteemed colleagues in the field of mental health research.

Before delving into my vision of the future for mental health, I’d like to briefly talk a bit about myself as a person. I am Jahn Jaramillo. I am 34 years old. I was born in July. So, that makes me a cancer. I am emotional. I am loving. I’m a son and a brother. I’m someone who loves to learn and is curious about the world and appreciates human connection in all its forms.

I also possess intersecting identities. I’m Latinx. I’m a Colombian immigrant. I’m bilingual. I’m gay. I am someone living and thriving with HIV. I am a survivor, which leads me to my career trajectory.

I’m currently a Ph.D. candidate at the University of Miami, working on ending the HIV epidemic in South Florida. My research focuses on Latinx sexual minority men and developing strategies and programs that support our health and wellbeing in the areas of sexual health and mental health.

Recently, I was awarded an F31 grant to culturally adapt an evidence-based employment as HIV prevention intervention aimed at addressing the structural factors driving HIV disparities among immigrant Latino men who have sex with men in South Florida.

This project involves gathering feedback from the community and experts in HIV prevention, employment, and mental health to ensure the intervention is culturally grounded for Spanish-speaking Latino men with recent immigration histories.

My goal through this research is to unpack the diverse needs of subgroups within the Latinx community, ensuring we are not treated as a monolith, but rather receive the care that is tailored to our specific needs, preferences, and circumstances.

Additionally, I aim to make the intervention status neutral, focusing on meeting the needs of a disproportionately impacted subgroup within the Latinx community, one that often faces marginalization and erasure within the healthcare system.

Before I move on, I want to add — and I wrote this down — I received a perfect score on this F31 grant. Beyond — thank you very much — beyond being immensely proud of myself, I’d like to share that for me shows in so many ways that projects like these are not only needed but have huge relevance for the communities that it’s trying to serve.

In thinking about this year’s theme, Celebrating 75 years of Research Discovery and Hope, I’d like to share a story about a recent experience that profoundly shaped my vision for the future of public health at the intersection of sexual health and mental health for communities that I’m a part of and that I wanted to support and protect.

This past summer, I attended a summer intensive program in Intersectional HIV Science at Northwestern University, which invites yearly, a small cohort of trainees in the behavioral and social sciences who are Black, Indigenous, and people of color, as well as sexual and gender minorities to attend a series of lectures and workshops.

I met such cool people there. And for the first time, I was in a space where the queer nerd in me was fully accepted. I could nerd out with colleagues who profoundly understood me, something I’ve never had access to in my life. I went too fast.

On the top left, we have Wei in red, who was recently hired as a professor at a top university in California and conducts research with queer communities in China. Then there’s Alex with glasses who develops at-base interventions for LGBTQ+ communities. And Cris on the far right, a sexologist who supports queer and immigrant communities in Arkansas.

We were able to connect through our intersectional identities and build meaningful relationships with other queer academics, including some who were open about living with HIV. Seeing them as role models meant so much to me at this point in my life.

Participating in such an affirming space allowed me to deeply reflect on the future of public health and mental health for our communities. In that space, I began to think about three critical areas for the future.

One, a vision for future health research priorities that I would like to see. Two, a vision for supportive structures to help scholars like me further develop. And three, a vision for community being central to the future of mental health research.

First, regarding my vision for expanding future health research priorities, I believe it is crucial that we broaden our research agenda to focus on other specific areas related to human sexuality, LGBTQ+ health, and the health of Latinx communities.

This means engaging gender and sexual minorities who are often overlooked, particularly those who do not fit in traditional categories like cisgender or monosexual to ensure that all communities under the LGBTQ+ umbrella receive the resources they deserve.

Too often, these groups are left out of research initiatives, which leads to limited resources and tailored interventions that truly address their needs. For example, we need more research focused on the health of bisexual individuals, transgender people, and other underrepresented groups such as immigrants and Indigenous or First Nations communities, people who have historically been underserved and who often do not participate in or are excluded from research initiatives due to deep mistrust of institutions who have harmed us.

Expanding our research agenda in these areas is not only necessary but urgent. By addressing the needs of diverse communities, we can create a more inclusive and equitable healthcare system. It is important to deconstruct broad terms like LGBTQ+ and Latinx to ensure that all groups within these communities receive the resources that resonate most with their values and their realities.

Nuanced, culturally-responsive research is essential as generalizations can lead to missed opportunities for effective care and support. This requires moving beyond simply collecting data or using white populations as a default comparison group.

Instead, we must rely on and truly listen to LGBTQ+ and Latinx communities, prioritize their stories, and allow their voices to shape the research agenda in ways that directly reflect their unique experiences and needs.

Second, my vision for building supportive structures for scholars and supporting the pipeline, which we spoke about before, involves doctoral students and scholars like me who are dedicated to making a change.

Additional efforts are needed to develop better infrastructure for minoritized scholars who often face challenges unique to their experiences. I propose an NIH-sponsored conference for early career researchers, including recipients of predoctoral grants like the F31 or T32, especially those from minoritized groups or working in niche research areas.

Too often NIH institutional initiatives to support underrepresented minoritized scholars target postdocs or junior faculty only. However, reaching out to predoctoral and other graduate students earlier in the pipeline could be game changing.

Academia can often feel isolating, especially for those of us who represent the communities we aim to serve. Navigating academia of both a scholar and your authentic self, whether LGBTQ+, a person of color, or someone living with HIV, can feel like walking a fine line between pride in your identity and the fear of rejection.

I have experienced that isolation firsthand in moments where I questioned whether I truly belonged in spaces that didn’t feel like they were made for me. How many of you have felt the same? I know I have.

There’s an unspoken element of shame and stigma that often forces scholars to hide parts of themselves or retreat into isolation. That’s why creating additional resources and spaces for scholars like us is not just beneficial, but necessary.

These spaces could provide opportunities for us to come together, not only to share our research, but to affirm each other’s identities or lived experiences. We need places where we can build community, feel seen and valued, and know that we’re not alone in our struggles.

When we have spaces to connect with one another, we become more resilient, more empowered, and more capable of making meaningful impact both in academia and in the communities we care so deeply about.

The conference I’m envisioning could include targeted leadership training, peer mentorship programs, and professional development workshops to help build a strong network of scholars.

For example, imagine an annual event where students like me, those working in mental health, HIV research, and LGBTQ+ health, can come together not just to present our findings, but to build lasting relationships, to share tools and resources, and to ensure we are supporting each other throughout our careers.

As researchers, we often talk about peers and centering people with lived experiences at the forefront of HIV and mental health research initiatives. The focus on communities should also extend to the scholars themselves who are conducting the research, supporting their mental health, given the proximity to the communities they partner with, and the shared experiences they have with communities.

Fostering bidirectional support between scholars and community can create a healthier, more sustainable environment for wellness. And lastly, my vision for community comprises a world where research is co-created with communities, where they not only participate, but ultimately take ownership of the research process.

This approach ensures sustainability. When communities are deeply involved, the research becomes more organic. And dissemination happens naturally because they understand and are invested in the outcomes.

In an ideal world, research with Latinx and LGBTQ+ communities would no longer be something that is done for them. Instead, our communities would be leading the change, setting the research agenda based on our lived experiences, and defining the outcomes that matter most to us.

What does this look like? This process would involve creating research projects where the community partners are involved from the beginning, helping to identify the research questions, decide on the methods, and interpret the results. And beyond that, the findings would directly benefit the community, whether by improving services or empowering folks with the knowledge to advocate for their needs.

In closing, today is a day for celebrating the incredible work done in mental health research and the contributions each one of you has made in the service of others. Everyone here has their why and the driving force that unites us under a common goal, mission, and vision for the world we want to see.

As we celebrate 75 years of research, discovery, and hope, let us look ahead for the next 25 years to a future where our vision for mental health has become a reality. I celebrate our shared passion for research, not for knowledge alone, but for helping others.

Without these efforts, we wouldn’t be — we wouldn’t have the lifesaving treatments like the ones keeping me alive today, allowing me to stand here as a dreamer and as someone committing to making a positive impact in the communities I belong to.

As I reflect on the past to understand where I’ve come from and how far we’ve come as a field, I also look forward shaping my journey as a scholar, a person, and a human being in pursuit of a brighter, more equitable future.

I look back to when I first immigrated from Colombia to that moment at JFK Airport — I know I look cute [laughs]. And to my childhood self, eager to learn, to that little boy, I say, “Done. You’ve got this, papito.”

Our stories will shine. They will be heard. They will resonate in your research and why you do what you do to help others to make sense of the world, to alleviate human suffering, and to create a better world for all regardless of who they are, ensuring that they have access to quality care and the tools they need to thrive.

I’d like to acknowledge the mentors, my family, and the organizations that have supported my personal and academic journey, including the NIH for giving me the opportunity to dream and to work towards a better tomorrow.

Thank you all for taking this moment to listen and for your own contributions to the field of mental health. Let’s not just envision, but actively build a future where both scholars and the communities they serve, especially LGBTQ+ and Latinx communities, thrive and where mental health research is not only done for the people, but with them.

Together we can ensure that every person, regardless of their identity, has access to the care, resources, and support they need to live healthier, fuller lives. I have attached my email should anyone listening want to reach out. And thank you so much for this opportunity.

ALESSANDRA ANGELINO: Hi, everyone. Can you hear me okay? All right. Jahn, that was a beautiful presentation. And I’m super inspired going forward into chatting a little bit about Indigenous adolescents with you all. But really, I think we could all just leave right now because that was super powerful.

It is lovely to be joining you all today virtually. I’ll be talking about ways we can support the mental health of Indigenous adolescents in the United States looking forward into the future.

I have listed my affiliations here, and I don’t have any disclosures. And before I begin, I also wanted to acknowledge that here in the DMV, we are the guests of the Nacotchtank and Piscataway peoples.

And I ask everyone to consider how daily, we engage in the processes of establishing and strengthening the relationships with the Indigenous peoples where we live and work.

I also want us to acknowledge the history of genocide and ongoing systemic inequities as a step towards reconciliation with Indigenous individuals. You can check out the link at the bottom of this slide to learn more about whose land you’re on.

In this presentation, I’ll cover how Indigenous youth can be seen, heard, and celebrated as we’re looking forward into the future of mental health. The four main topics I’ll discuss are culture as medicine, data sovereignty, planetary health, and traditional knowledge.

I’ll begin with culture as medicine. I first want us to think about the concept of culture as a method for healing and prevention. This has implications for both physical and mental health, and for Indigenous peoples, is really tied to context, namely historical traumas, subtler colonialism, and systemic marginalization that continue today.

These have led to significant disparities for Indigenous communities, primarily by ripping people away from their culture and their connections. Over time, as people have reconnected with their culture and community, we’ve seen a lot of revitalization and healing.

This is relevant in the setting of the current mental health crisis, where Indigenous youth have higher rates of suicidality and mental health diagnoses compared to any other race or ethnic group in the country. Thus, thinking about ways that we can view mental health intersectionally, especially incorporating culture, is critical.

Intersectional care also recognizes that the methods of care that we traditionally use in the dominant Western model are not relevant or effective or appropriate for Indigenous folks. And so, thinking about how we can promote opportunities for culturally-centered care is really important.

Using culture as a tool for mental health can look like incorporating traditional language in the health encounter, even language learning itself, and utilizing spirituality, traditional medicine, and connection with the land in mental health care. Recruiting and retaining providers who are Indigenous also supports improved mental health for this community.

So, why now? Clearly the concepts of trauma, marginalization, and connection with culture have been important with this community throughout time. But in the last decade, we’ve seen a demographic shift in the American Indian and Alaska Native communities towards a larger youth and adolescent population.

Since the pandemic, as I alluded to earlier, there’s been increasing mental health needs. So, I invite us to contemplate how we can really tap into culture as a tool for prevention as well as healing, as we continue to see this youth population expand.

I wanted to share a model program for indigenizing health promotion carried out by the Northwest Portland Area Indian Health Board. This program focuses on gender diverse and two-spirit youth in particular.

And one of the things that we’ve seen is that by highlighting the historical presence and reverence of people who were gender diverse over time, youth are able to reconnect with this history and culture and have improved mental health and wellbeing.

So, you’ll see in this image here, it’s really highlighting that concept of we’ve always been here, and we’ll always be here. And then I have some images from recent events for the Indigenous two-spirit LGBTQ community that also served as opportunities for connection.

And so, this was just a two-spirit gathering on the left and on the right, the Indigiqueer Joy Festival with the drag competition that was held in June.

Getting into a little bit more nitty-gritty in terms of details for mental health care that I’ve been working on with the Northwest Portland Area Indian Health Ward. We’ve been utilizing the term Indigenous, gender-affirming care to really incorporate the current standards of care for gender-diverse individuals, plus Indigenous well-being, and concepts of mental health.

So, this really allows folks to kind of have, again, that intersectional model of care and feel more safe in the environments they’re seeking care in. It also means accounting for the fact that the diagnosis of gender dysphoria is based, again, on this Western cultural framework where a binary is the norm.

So, instead we’ve been using this term gender embodiment, which a lot of our two-spirit folks have actually led us down that path, which can really look like a constellation of cultural, anti-colonial treatments.

So, for some folks, it looks like having a therapist as well as a traditional healer for mental health ceremony. It could also look like a care plan that has medical medications as well as herbal treatment for anxiety.

Moving on to the next topic, data sovereignty. This concept highlights how each — sorry, little slow to advance — highlights how each tribal nation has the authority to administer, collect, own, and apply data in the way that they choose.

This is rooted historically in each tribal nation’s constitutional right to govern its own people, which is unique from other minoritized groups. Attached with this is this concept of decolonizing data.

For Indigenous folks, it’s the process of reclaiming data and research, ensuring the inclusion of Indigenous folks, and recognizing the inherent strength of Indigenous pupils. Connecting it to mental health, first and foremost, acknowledging how research and care have been tied to harmful practices, and then coupling that with restorative practices are key.

For mental health in particular, focusing on centering Indigenous perspectives and mental health care is important. So, again, what does mental health look like for an Indigenous person and communities? Similarly, focusing on strengths and resilience and highlighting protective community factors is important.

Lastly, making sure that we’re properly reporting race and ethnicity and mental health conditions are critical. There are some cultural traditions and beliefs that sometimes can overlap with mental health conditions, at least in their presentation.

And so, care must be taken to really understand what the cultural practices and beliefs are prior to making an erroneous diagnosis. Without accurate data, communities who’ve been systemically included will continue to face exclusion in the mental health realm.

Similarly, when we’re thinking about the future and data, I like to think about AI and other machine learning models and especially thinking about what is actually important and meaningful to tribes in terms of data in solutions and what data already exists, so, in this way, thinking about leveraging existing data sources in line with Indigenous principles to yield better outcomes with, again, what non-Indigenous folks are doing.

If tribal nations continue to be excluded from these processes, we’ll lack data, they’ll lack data, AI lacks data. And then ultimately, we’re just having less solutions that can be created. I’m personally still trying to figure out AI myself, been experimenting with ChatGPT, and just putting some basic questions about the work that I do, about, you know, very simple things that we all should be learning in elementary school about Indigenous communities. And there’s not much.

So, we really have the power as researchers to bridge the gap by partnering with Indigenous communities, fostering data sovereignty, and promoting the ethical use of these data as well as technology to improve mental health. And again, make sure that we’re continuing to allow Indigenous folks to have a voice.

Moving on to planetary health and its role in mental health, I wanted to bring up this idea of Indigenous traditional knowledge. Today, about 80 percent of the world’s biodiversity is on Indigenous land. And so, over time, Indigenous folks have really developed this unique understanding of the relationship between humans and ecosystems, especially that connection between the land and spirituality and wellbeing.

Because of this and because of the intergenerational passage of knowledge, Indigenous folks, including youth, are uniquely positioned to adjust challenges today. I bring this up because a lot of health risks, including mental health risks, are tied to this close relationship with the land, which is, as I mentioned before, strong for Native folks, including associations with traditional diet, medicine, health, and spirituality.

Forced displacement of Native folks has altered these relationships. And so, again, Indigenous populations are really more susceptible to the health impacts of climate change.

For mental health in particular, Indigenous youth report high rates of climate grief and anxiety, in addition to other mental health issues that stem from historical losses and trauma as they’ve directly experienced climate-related catastrophes and degradation.

Currently, Indigenous youth have limited power in decision-making spaces. They’re often misnamed or just not included or included as the other group. And so, in climate change policy, in research, in mental health, we’re really not tapping into the power of those youth.

On the contrary, youth who have been able to participate in climate change work have improved mental health and hope for the future. So, I just wanted to leave us with thoughts about how we can really support Indigenous youth and adolescents in climate advocacy to improve mental health, especially building on that traditional history and that inherent knowledge that they have.

And lastly, traditional knowledge is critical for mental health. Research in Indigenous communities has shown that historical losses, as well as strengths, as I mentioned, are tied to mental health. We know that access to traditional healing methodologies and traditional healers can improve mental health outcomes. And I’ve listed some of those ceremonies here as well as traditional medicines.

As a result of this, there are many opportunities for us to think about how we can utilize traditional knowledge to improve mental health across clinical research and policy settings. Thinking here — this is kind of just summarizing that again. But I just wanted to pull out some of the images here.

A lot of the traditional healers that I’ve been able to meet and work with are well integrated within a rounding team in the hospital. Or instead of seeing a therapist alone, folks will see a therapist and then go see a traditional healer within a one-hour slot, which is a separate issue.

I know most of us don’t have one hour, but just recognizing how that access is really important. And I think it’s something that, in the way that our health system is set up and our research system is set up, we’re not really thinking about the importance or the impacts of that.

So, moving into the opportunities. From a clinical standpoint, thinking about how we can expand mental health services for Native folks within existing health systems, but in particular, increasing access to those traditional providers, both on and off reservations.

Currently, reimbursement for these traditional healing services is not possible. And so, advocacy on this front to CMS and other payers would allow for payment to those providing culturally-safe services.

Building opportunities for youth to also find community with a focus on tradition can also improve mental health by building self-esteem, self-identity, and again, building that network for support.

From a research standpoint, this summarizes a lot of what I spoke about in that data sovereignty section. But again, to summarize, inclusion, inclusion, inclusion, focusing on strengths, community-based co-design, and tribal sovereignty.

And then from a policy standpoint, really thinking about, again, advocating for inclusion. I think here education is important, since we’re not learning about Indigenous folks, let alone Indigenous health, let alone mental health at any level of education.

So, thinking about how to incorporate knowledge of historical traumas and mental health to build context as well as increasing funding opportunities focused specifically on Indigenous mental health would have a significant impact.

Creating parity between Indigenous traditional practices and Western medicine and mental health, both guidelines and research, I think also is great. Especially because it would increase buy-in, it would increase culturally-safe care, and also just patient safety, as well as the ultimate goal of improving mental health overall.

So, I hope that this brief talk has allowed us to reflect on ways that we can better see Indigenous youth, hear Indigenous youth, and celebrate Indigenous youth across our nation as well as internationally.

By upholding culture as medicine, the principles of data sovereignty, and by recognizing the impacts of planetary health and traditional knowledge on mental health, we really can work together with Indigenous youth and communities to reimagine and revitalize Indigenous mental health.

And with that, I just wanted to leave a brief shout-out here to the Paths (Re)Membered Project, which has culturally-safe, culturally-specific resources for two-spirit youth which is my main passion.

There’s a free telehealth medical — mental health service run by the program, where youth can just request help. And all the therapists are Indigenous, which is really wonderful. And so, I included that there along with the Instagram and text message page.

But, yeah, I would appreciate everyone listening, appreciate the flexibility to do this virtually, and I hope we can connect in the future. Thank you, everyone.

BRITTANY RUDD: You guys feeling inspired yet? I know I am. Okay. So, I am honored and thrilled to have the opportunity to share my vision for the future of mental health research at NIMH.

It’s my belief that in order to move the needle on mental health, we need to envision a community-engaged public health approach. This title was inspired by a quote that many of you may be familiar with.

When NIMH director, Dr. Tom Insel, left NIMH, he was quoted in Science magazine saying, “I spent 13 years at NIMH really pushing on the neuroscience and genetics of mental health disorders. And when I look back, I don’t think we moved the needle in reducing suicide, reducing hospitalizations, and improving recovery for the tens of millions of people who have mental illness. I hold myself accountable for that.”

And so, I hope to spend the next 15 minutes sharing my vision for moving the needle on mental health. But before I begin, I want to acknowledge and thank my incredible thought partners in this work. This is my research team, my community partners, my mentors, and my funders.

I’m going to start by explaining what I mean by a community-engaged public mental health approach. I’ll share how my lived experiences have shaped my vision for this approach. And then I’ll provide an example of this approach from my work.

So, it’s impossible to reduce and eliminate bias from our research. My lived experiences with power, privilege, and marginalization influence my lens and thus, my research lens. And so, rather than hide that, I embrace it. Because my lived experiences are important information, inspiration, and activism.

And so, important lived experiences for me are that I’m a White woman. I’m a preacher’s kid from a low-income community. I’m a mother, and I’m a licensed clinical child psychologist in an overwhelmed outpatient mental health clinic on the west side of Chicago. And so, as a practicing child psychologist, I’m keenly aware of the mental health crisis that we have in the United States.

Suicide is the second leading cause of death among young people today. This is not okay. I, like many of you in this room, have experienced the loss of someone I love to suicide. Our kids are not okay. And we who’ve lost ones to suicide are not okay. And we have a crisis on our hands among Black youth.

So, this graph is the rate of suicide by race. The orange is Black or African American youth. White are in green. Blue is for all. These are all too high. [laughs] But what I’ll point out is that while things are declining for white youth and overall, they are precipitously increasing among Black youth. And one of the things we are not doing well is reaching kids who need care.

So, this is a map of professional shortages across the United States. The darker the blue, the greater the professional shortage for mental health care. Very few places have the care that they need. And these shortages are getting worse, not better.

And while most youth who need mental health care never get it, when we ask the question, who gets evidence-based practices, the numbers are dismal. Many folks aren’t benefiting from these NIH investments in innovation. Maybe 3 to 10 percent. And that’s because most implementation efforts fail.

And one of the main reasons they fail is because the needs of the end user were not adequately considered in the design of the treatment, which is where the field of implementation science comes in. The field –implementation science is the scientific study of methods to promote the systematic — woo. Can you hear me better now? [laughs]

The systematic uptake of clinical interventions and programs into routine practice with the goal of improving mental health. It’s about moving the needle on health. It’s about turning NIMH investments into impact.

And from the field of implementation science, we know that we need to design with the complex service setting and consumer in mind. Hopefully, you’ve heard that enough today, [laughs] that that is what we need to move the needle.

We need community-based participatory designs where we co-design with the people who will be using the interventions and benefiting from the interventions. Okay.

So, you might be thinking, fine. Great. So, what we need to do to fix the mental health crisis is we need to hire more mental health providers. And we need to use implementation science to ensure that we’re getting interventions to the people who need it.

But I want you to pause and think for a moment. What — for every other public health crisis we’ve encountered, when it was cardiovascular disease on the rise, did we focus on making sure we hired more — hired and trained more cardiologists? Or did we think about preventing cardiovascular disease?

And what I’ll argue here today is we need a paradigm shift away from developing interventions and doubling down on prevention. And so, that’s where I’ll spend my time today talking about how we need public health for this public health crisis.

So, my lived experience — well, nope. Skipping ahead. What is a public health crisis [laughs] approach? So, a public health approach to mental health is not a new idea.

Some of my colleagues, Dr. Mark Atkins, and Stacy Frazier, argued for the need of a public health approach over a decade ago. The idea behind a public health approach is that we have levers of change across the spectrum from prevention to intervention. And at the universal level, we make sure that the interventions that promote health are available to everyone in the community.

At the targeted level, while we’re promoting health, we’re also targeting those who are at greatest risk for developing illness. So, at the universal level, think of things like fluoride in the water or think about the law to wear a seatbelt. It benefits everyone. At the targeted level, think about breast cancer and colon cancer screening for those who are at greatest risk by age, for example.

And then once we have spent all of our energy that — or all the energy we can on prevention, then we make sure we have cutting-edge treatments available to target illness. So, voila, community engaged public health, where we centered the needs of community while we seek to focus on prevention.

But what could this look like operationalized for the mental health field? And that’s where my lived experience has really shaped my vision. So, I grew up in a small town — a small rural community, Corcoran, California. It is right in the middle of California’s Central Valley. And it claims to be the farming capital of the world.

And farming is one of the largest employers, [laughs] but so are state prisons. There are two in Corcoran. There is a drug rehabilitation center and a maximum security prison, where Charles Manson lived for 30 years.

And so, as a preacher’s kid, you’ll probably imagine that finances were pretty lame. But that was the common experience for kids in my community. Twenty-nine percent of people in Corcoran live below the poverty line, which is double the national average. Forty percent of kids are living in poverty. I brought the water because I knew I’d get nervous. Okay. So, pause and breathe.

Okay. So, in our country, individual wealth determines your access to opportunity. Because kids in my community were living in poverty, our access to opportunity was limited. So, the Child Opportunity Index measures and maps the quality of resources and conditions that matter for kids’ healthy development in the neighborhoods where they live and where they play.

And so, this is the Child Opportunity Index makes up things like quality education, access to safe aftercare programs. And so, this is a map of the child opportunity indices for the top 100 biggest metros. Blue is greater opportunity, and red is lower.

Corcoran has the lowest opportunity index in the entire country. So, in the United States, marginalized youth live in areas with the least access to opportunity. I don’t know if this has a thing.

But you’ll see here that white youth, who are in the aqua and orange — yellow are concentrated in very high and high opportunity neighborhoods. Where Black and Brown youth are concentrated in our country in very low and low opportunity neighborhoods.

Corcoran has the lowest opportunity index because 87 percent of our population is Black or Brown. And so, I had a firsthand seat to see the impact of living in a disadvantaged neighborhood, the impact that it had on my friends, on my peers.

So many of the kids I grew up with developed mental health illness, dropped out of high school, started using substances, and ended up in the juvenile legal system. And that’s because our access to opportunity influences and shapes our mental health and wellness.

Your neighborhood influences how long you will live. It also influences our mental health. So, to move the needle, we need to ensure that all children have access to opportunity-rich environments. And we can look to Bronfenbrenner’s model to kind of start to think about where we want to target.

And so, we need to be thinking about embedding interventions in schools, supporting parents. We also have a parent mental health crisis on our hands. Supporting parents, making sure every child has access to quality education. Supporting churches and spiritual leaders in promoting mental health in our communities.

And the good news is that we have a ton of research on universal interventions that can promote mental health in the neighborhoods and the communities where kids live.

The tricky little problem is implementation. What I’ve said before is that your individual wealth influences your access to opportunity. And so, in order to start seeing a change here, we have to figure out ways to decouple individual wealth from opportunity. Which is why we need more research on how to promote evidence-based policymaking; another theme that we’ve heard throughout today.

And this is an emerging area, but we need more research to understand how to do this well. Okay. So, at a universal level, we need to foster opportunity-rich environments for everyone. But what about at the targeted level?

And this is where I’ll argue, we have to think about the legal system. Kids touched by the legal system, child welfare, juvenile legal, are at increased risk for the development of psychopathology. I’ll focus in on the juvenile legal system because kids in the juvenile legal system are four times more likely to end their life by suicide than their peers.

And suicide is already the second leading cause of death. Kids who are detained — 50 percent of kids who end up detained think about ending their life. And while we have guidelines to support the implementation of suicide prevention in these settings, my research demonstrates that we are not implementing them well.

So, this is a graph of 10 detention centers in one state. The y-axis is the percentage of the guidelines the center implemented. And you can see that most didn’t even implement half. So, my cousin, who died by suicide, he died the day that he left detention. That’s a life we could have saved.

So, to move the needle, we need targeted prevention in the social systems that serve highly vulnerable youth. And I have been very fortunate to be able to take a community-based participatory approach to my early career award, where we’re trying to operationalize a zero suicide model for juvenile detention.

And in this work, we’re centering the needs of Black youth because as I said earlier, we have a crisis on our hands among — for suicide among Black youth. And unfortunately, because of what I said earlier about the funneling of Black and Brown youth into communities where there are very few opportunities, youth in the juvenile legal system are — Black youth are overrepresented in these settings.

Across these figures, you’ll see that Black youth are more likely to be touched by the juvenile legal system, whereas white youth are more likely to be diverted. And Black youth are more likely to be detained.

And in doing this work, we are partnering with community organizations that do this work day in and day out, who center the needs of Black youth every day. Like BUILD, Chicago, which is a nationally recognized anti-gang, anti-violence, youth development program. And together with BUILD, we have a youth ambassador program of young Black people who are motivated to end suicide in their communities.

And so, these young people have met with us in a reoccurring fashion to eat pizza and develop a vision for ending suicide in their community, especially among youth touched by the juvenile legal system. Together, we have this vision for aim one of my project — our project.

We want to know, from the perspectives of young Black people with previous involvement in the juvenile legal system, how can we prevent those in crisis from becoming system involved and detained so that we can develop universal interventions? How can we improve suicide prevention across the juvenile legal system so that we can develop targeted interventions?

But our hope and dream together is that our universal prevention becomes so effective that we won’t even need the juvenile legal system interventions anymore because they won’t be needed. The juvenile legal system won’t be needed.

And so, I could go on and on and on about the impact that these young people have had on my science, on the work, on my joy. But what is truly magical about community-based participatory research is how it can also be radically healing.

And so, these young people have worked with us. And this is not an intervention. This is a research project. And as a result, they’re saying things like, “This helped my mental health. And now, I can help other people with theirs.” “I learned from this — being a part of this research that you can have — be struggling with mental health and not even know it. This work taught me words I can use to talk with other people about their mental health.”

So, research — CBPR can be healing and transformative. Okay. So, my vision for the future is a community-engaged public health approach. And what I’d love to leave us with is thinking about, what if NIMH’s funding for research mirrored this triangle? Where we focused and funneled our resources on a paradigm shift towards prevention. Where we were really focusing in on community-based participatory work and implementation science so that we could double down on prevention.

And maybe then, the current supply of providers could finally meet the demand for services. I want us to end with a quote from Desmond Tutu who said, “There comes a point where we need to stop pulling people out of the water. We need to go upstream and find why they’re falling in.”

And so, I hope over the next 25 years, we can build a fence around the river with a community-engaged public health approach. Thank you.

OLADUNNI OLUWOYE: Hi, everyone. Hope you all are doing well. My name is Dunni. One of the nice things about going next to last is that you get to really see that your slides are really dry [laughs] compared to everybody else’s slides that look fantastic and have covered fantastic topics and conversations.

And I really have left also feeling inspired by all of other presenters that have come before me. So, my slides are called Thinking Upstream: Equitable Mental Health Services and Research. I am an early psychosis researcher.

And so, a lot of what I’ll be talking about will be planted and grounded in early psychosis work but could be applicable to other areas as well. So, as many of you may know, there’s been major advancements in the improvement in the level of care for individuals in the early stages of psychosis. Especially here in the U.S. through the form of coordinated specialty care programs.

Because of the initial push and investment from the National Institute of Mental Health, we have seen a proliferation of coordinated specialty care programs throughout the United States, with over 350 programs being implemented. And I’ll get to that next point.

But despite the success of — or the relative success of coordinated specialty care programs in improving the outcomes associated with early psychosis, we still see disparities and inequities in care. And in the types of research that is being conducted with individuals in the early stages of psychosis.

And I want to say that the disparities that we see in terms of low service utilization prior to get into coordinated specialty care. More difficult pathways for individuals in the early stages, especially those from historically minoritized groups and underserved communities. Disparities in engagement once individuals actually get to coordinated specialty care programs.

These disparities and inequities are not new things. They’re not revolutionary things that we have just now identified in the past 14 years. We always and have tended to see low engagement, more difficult pathways to care for individuals from ethno-racially minoritized backgrounds and underserved communities where we just see low service utilization.

And part of the reason potentially, that we continue to see the — these disparities that are not unique to early psychosis care is simply because we choose to develop interventions to address those disparities at the individual level. Rather than thinking about community-based interventions to address the inequities that are driving the disparities that we see through care.

If you all did not have the opportunity to see the opening talk for this series, you should go back online and really see the presentation from Ruth Shim, who really broke down disparities and inequities. And what’s driving those different things, which is a fantastic talk.

So, my — I have been tasked with thinking about, where should we be thinking? Where should we be going? And part of that is tailored to disparities and considerations that we need to take into account that I believe are driving some of the disparities that we see downstream.

So, the first one is cultivate and diversify. In early psychosis work, there was a recent study published in psychiatric services that alluded to the fact that there was limited diversity and lived experience in the leadership of individuals that have been funded through EPINET. That article just was recently published in — what are we in? 2024? 2024.

Prior to that, there has been an article also published that really spoke about only 13 percent of first authors being published in early psychosis work in leading journals in the United States. And that’s 13 percent of individuals from ethno-racially minoritized groups. To the point where, if I want to go down to the nitty gritty, the article even mentioned that there was zero percent of Black authors first authorship for papers in early psychosis in these leading journals.

So, a common thread that we have seen today is really focusing on the training and the mentorship of individuals along the pipeline. We have a leaking pipeline. I have been speaking to multiple people that have — are presenting today about this leaky pipeline. And this is not a leaky pipeline that just started to leak one month ago or two years ago or five years ago.

It is continuously leaking where even in conversations that I’m having until this day, individuals are saying that I do not want to be in academia anymore. And I think it was Brielle that had mentioned it when she was given her presentation. When she looks up, there is very limited number of individuals that are female, that are Black, that are full professors.

And that has a trickle-down effect. So, this figure that you see on the right, which looks blurry from my end, but hopefully, it’s not blurry for you all and really gets home the point, is that we need to be intentional. We see differences in our level-funded grants, in fellowship level-funded grants, in training level-funded grants.

And this isn’t very — this isn’t specific to the National Institute of Mental Health. This is for the National Institute of Health. And these do not change. And so, that’s one area that we need to be intentional on. It is not enough to simply encourage applications from underrepresented groups.

There needs to be specific mechanisms that are specifically tailored for training and the mentorship of individuals at multiple different stages. From graduate level to postdoc, even to junior investigators or early stage investigators already in academia.

The second part of that maybe touches on what Brittany had said, and I think other people have said as well, is the majority of the interventions that we are creating are not delivered by PhD-level individuals or MDs in community-based settings. They are being delivered by social workers. They are being delivered by licensed mental health counselors. They are being delivered by paraprofessionals.

And so, there needs to be added support; a, to engage individuals while they’re in school in order to go into early psychosis and coordinated specialty care programs. Because even though we’ve seen an increase in those programs, we have also seen a lot of those programs ceasing exist purely based on a shortage of staff and the ability to provide services.

So, my task for that is really thinking about there are mechanisms that are in place to support individuals who are interested in research. Those mechanisms need to be in place that plays an investment to have individuals think about having a career in community behavioral health settings.

Those things don’t just impact the services that are being delivered to the individuals that we care for. But those things also impact the research it is that we are trying to do. That also happens to be a lack of focus in implementation science.

We rarely see, in a lot of articles, the race and ethnicity of providers delivering the services that are being implemented in programs. And so, that’s one area to address.

The second part, which has been also a common thread, is more community-based and partnered research. In the field of early psychosis, there has been very few studies that have been developed that have been community-based and truly community-partnered work.

It is not enough just to say that you have a community advisory board and then your work is community-based work. It’s also not enough to think about, we know that these disparities exist. And yet, there are very few studies focused on specifically ethno-racially minoritized groups and underserved communities in early psychosis that have used community-based participatory methods.

So, one thing to consider is a restructure of the R01, one that takes into their account; a, it takes a lot of time to build trust in communities that have been historically mistreated. And have a lack of trust in researchers and in academia.

Part of that is also due to the fact that on the sustainability end, when the research is done that most researches are done. And that information is not being funneled back to the communities that have eagerly participated in those studies.

And so, while this looks like an arrow, it actually should be a continuous feed-around loop. So, is it that much to say, can we restructure an RO1 that includes additional time for the building of trust in communities, but also builds in additional time for the sustainability of the findings that come from that study.

So, it is able to feed back into the communities and then regenerate itself. So, that would be my one thing. Restructure the RO1, give us more money, more time. The third one is equitable implementation. We have seen over the last few years a lot of implementation science frameworks — lovely — a lot of implementation science frameworks be readapted to account for sustainability and equity.

This is a picture — but I’m thinking about equity in multiple different ways. This is a picture of currently funded EPINET science throughout the U.S. That’s the big — like, you know, the Shazam colors that you see. The little dots are the clinics that are participating in those EPINET programs.

So, one, are we actually reaching the communities that most — that may need to participate the most or would benefit the most from coordinated specialty care programs and learning health networks, which is what EPINET is. What you can see is that there’s a lot of area within the United States that is not covered.

And what you can also see that there are several programs funded in — on the East Coast. How much more can we know about the East Coast?

And so, one thing to consider is the continued investment of EPINET so that it adequately represents the United States and it captures individuals from different states. Because Black people and their experiences in the South are very different from the Black people that are residing in or are in New York and the experiences that they have.

And so, those nuances need to be captured. But part of that is being thoughtful about, who’s receiving funding? And, does it adequately capture and include individuals from various communities throughout the U.S.? My little bonus on the end is for all health services intervention. And that there is no point in creating an intervention if it’s not going to be implemented or it cannot be implemented. That is wasted money.

So, at the very least, all services and intervention research should include elements of implementation science. And if I would’ve taken a step further, they should probably, at the very minimum, be hybrid, type-one studies.

All right. Third one. Oh, no, fourth one. Last one. Collaboration. This is really for NIMH, is to leverage your position as a federal agency. We have heard from several different individuals. And I think there was also — Chyrell’s colleague also presented a question about sustainability.

And part of that is leveraging your position as a federal agency to elevate community-based interventions that have been successful, that are coming out of your portfolios. By being the bridge between a PI who may not know how to connect with a state level official. Who may not know how to connect with a department of housing or a department of transportation, in order for those policies to change, in order to make meaningful change.

That, I think, is one of the major things that is the biggest issue, is that we know that there are these upstream level determinants. There are things that are happening within communities. It is a lack of opportunity and limited resources.

And how do we actually make and invest in changes to the environment so that we can see sustainable changes in the long run. So, overall, it takes investment. It takes investment in order for there to be sustainable changes. And that’s where I’ll end. Thank you.

DANIEL HANDWERKER: Thank you. That was amazing, doc. You were more humble at the beginning to those — every one of our talks was amazing. So, I’m welcoming everyone up for a moderated discussion. I’ll also stress that if you want to ask a question, please go to the microphone so people online can also hear.

DAWN MORALES: Hi. My question is probably mostly for Dunni. Thank you so much for your talk. My name is Dawn Morales. I’m director for American Indian Alaskan Native and Rural Mental Health Research.

So, you recommended that the NIH consider restructuring the RO1 funding mechanism. And I would like to know, the NIH does have a number of two-part funding mechanisms, where the first part either automatically converts to the second half of funding. Or sometimes the person has to come back in for review formally.

But the first part, they are to establish feasibility or acceptability or to gather pilot data. There are milestones at the end of that first part of funding that are met that permit them to go to the second part.

So, I was curious to know what kinds of milestones you would recommend that we consider if we were to restructure that RO1. So, you suggested that that first part would be used to build trust. I think you had a couple of things. So, my question would specifically be, how would review at NIH know that those kinds of goals had been met?

DUNNI OLUWOYE: Is this on? Can — you can hear me. That’s a good question. I was just throwing things out there —

[laughter]

— and hoping that you would catch them. But I think that — since it’s been caught and then it’s been thrown back at me, I think that it’s — it could be multiple different things.

So, if I am — I would — I’m still in early stage. I want to be in early stage. If I’m an early stage investigator and I am in academia, and there’s a tension between things that I have to do academically and things that I want to do because I have a passion for it.

Then part of that is it allows built-in time to cover my time as a researcher. As well as time to actively seek out different partnerships within a community. And so, it wouldn’t necessarily be that there would be an exact measure of trust. What about could it be, how many group organizations want to participate within the community? That could be measured.

Another thing that could be measured is, how many community advisory boards meetings did you have? And the attendance rates of those community advisory boards. Because people can have them and then you could still have like 20 percent attendance. And so, that could be measured. And so, that allows for, a, a place for co-production and co-design.

And so, those milestones are in place. And then you have your regular RO1 that you’re building out. And the same thing for sustainability.

There’s — in the human subject’s portion of a — when you submit a grant, you’re asked to think about dissemination. But is — are you writing that in a very meaningful way in terms of how you’re going to disseminate? Or are you just saying, “I’m going to publish my four articles and then X, Y, and Z?”

But the sustainability plan is what plans do you have to engage city officials? If your findings are X, Y, Z, or even if your findings do not pan out that way, what is your actual plan? Do you have buy-in from that city official that they are even willing to meet with you about the study it is that you’re conducting?

And I think that there’s ways to build into that. And I think it’s also being mindful of the fact that, yes, there are other mechanisms, like an R61/33. But in the mindset of individuals, people are wanting the RO1.

It doesn’t matter if the R61/33 is giving the same funding — the same funding amount of money or the same amount of use. People are seeking out an RO1. Because we’re taught from we babies that you reach this milestone when you get the RO1, not the R61/R33 or the R34.

And I think that there’s ways to build that out so that it is meaningful. And it actually captures individuals that are truly doing the community-based and community-partnered work. Yeah.

DANIEL HANDWERKER: So, I don’t see any other questions in the hall right now. But I have a question then. Several of your talks talked about reaching people earlier and getting them before there’s a crisis. And it feels like a lot of policy and in practice and implementation is waiting for the crisis point — like its peak.

You know, even my kids, their extremely well resourced Maryland school system, when does the school provide service? When there’s a direct risk of a kid failing or leaving school, which is often too late.

So, how would you sort of push things earlier and say, you know, in all these areas, in all these community building, so that schools have a resource? Like, what would be your dream for like how we reach kids earlier before they’re at that crisis point of like, hey, you’ve started failing classes? Hey, you’ve had an episode of psychosis in school.

BRITTANY RUDD: So, I think our — the way in which we approach mental health is very much based on the fact that we can get reimbursed for clinical services that have been deemed, you know, not FDA approved. I’m a psychologist.

But [laughs], you know, basically, poor clinical service delivery. And we don’t have similar mechanisms to think about prevention. And so, I think some of what we need to be thinking about is, how do we reimburse for the prevention aspect of things? How do we fund putting health in mental health rather than focusing on mental illness?

And so, I think, how do we make sure there’s been a lot of changes in Medicaid to think about some prevention? But we need more. We need — like why do I — why am I only able to bill for mental health services if I’m sitting in my clinic? Why can’t I go to the school? Why can’t we bill in alternative ways?

And I — so, I think there’s a lot of funding issues because there’s so much that goes undone and unsupported and unfunded. So, I think we have to rethink about promoting health rather than waiting for illness and funding that.

JAHN JARAMILLO: Hello? Hello. I’d like to chime in on that as well. In my work with Latino sexual minority men in South Florida, I think through our community advisory boards and our work — qualitative sort of work with them, it’s the same thought.

When we do bring this idea of mental health, in Espanol, it’s like, “No estoy en crisis.” I’m not in crisis, right? So, how do we take this public health approach to mental health and really bring it to communities that are at really high risk and are vulnerable to HIV, right? Are we only just focusing on HIV? And what does it mean to have an HIV epidemic, right? We know that that’s also connected to other epidemics.

You know, the syndemics, right? The concept. And so, these co-occurring sort of systems and how to create or develop intervention packages that really think about prevention in a more holistic sense of like, not only am I thinking about how to reduce HIV vulnerability among Latino sexual minority men.

But how do I incorporate wellness? And that also resonates with Latin Americans. That resonates with their language. That resonates with the ways in which they see stigma. And how they, at times, can — and we, at times, can bring that across to the United States if we’re immigrating. Which is another — something to consider in terms of this whole cycle of immigration as well. And what people bring and how interventions that are trying to reach communities like Latino sexual minority men should really consider sort of a mental health and prevention as well.

DUNNI OLUWOYE: You know, if I had a wish list, it would be that — like, I’ve asked participants, you know, what would be helpful? And individuals are like, “I would love to hear about it on the radio. I would love to hear and see it just as much or frequently as I see medication ads. I want to see things that really focus on stigma.”

It’s — there’s been numerous studies that have spoken to the fact that ethno-racial minoritized communities seek out informal resources prior to even getting into formal services.

And so, part of that is creating partnerships with local resources, like, the YMCA or community centers and educated individuals at those places. So that when people do get to those places, people are well informed and have the resources that can guide them to the appropriate settings.

And so, my thing is, do a national campaign and have like these famous people in there. And they’re all talking about, you know, things related to stigma so that people are just well aware and well informed.

DANIEL HANDWERKER: I think we have time for one more quick question.

DAVID DELAHUNT: Hey, guys. Dave Delahunt [phonetic]. Thanks for all your work. This question’s mainly for Alessandra but would love to hear anyone else’s perspective as well.

I’m curious your thoughts on the opportunity for increasing accessibility to traditional natural mental health medicine, such as psilocybin and peyote and ayahuasca. Thanks.

ALESSANDRA ANGELINO: Yes. That is a great question. I don’t know that much about those besides, you know, general colloquial knowledge. I do know that a lot of the healers that I’ve spoken with have a lot of qualms with them being used more commonly.

And just because there’s sort of that leap that happens between, how are we using these in a traditional way? And how are we misusing these in kind of appropriating them? Similar to using sage and smudge ceremony and like smudging and — that has a lot of spiritual meaning.

And so, for instance, yeah, you might see behind me like someone has gifted me a sage bundle. But since I’m not indigenous, I will not use that. However, now, they’re being mass produced. And, you know, people will kind of use them willy-nilly without understanding the meaning behind it.

And so, I have spoken with some folks specifically about psilocybin. And I think they’re excited about it. But I don’t think that one in particular comes up a lot in a traditional manner.

But along the same vein, I think there is a lot of openness to trying some of those complementary and alternative methods. But not necessarily a way to do things safely on a mass level. And then also, to have that reimbursement issue, which a few of us have alluded to.

DANIEL HANDWERKER: I’d like to thank again, all our speakers for all — and all — everyone here for your questions. I’d like to invite the panelists to return to their seats. And welcome up and NIMH’s scientific director, Dr. Susan Amara to introduce our closing speaker.

Transcript

SERENA CHU: Welcome back, everyone. If you could take your seats, we’re — I’m going to go ahead and get started. Good afternoon. My name is Serena Chu, and I am a scientific review officer in the Division of Extramural Activities. And it is my great pleasure to introduce the speakers to you today.

We — joining our panel will be Dr. Silvia Lopez-Guzman, who is chief of the unit on Computational Decision Neuroscience at the National Institute of Mental Health. Dr. Guzman received her M.D. from Pontificia Universidad Javeriana in Bogotá, Colombia, followed by her Ph.D. in Neuroscience at NYU Center for Neuroscience.

She also holds a joint appointment with the National Institute on Drug Abuse, where she is part of the Translational Addiction Medicine branch. Her lab studies the computational and neurobiological basis of decision making and how this process is altered in depression, anxiety, addiction, and pain.

Also joining the panel will be Dr. Alexandra Rodman, who is an assistant professor in the Department of Psychology at Northeastern University, where she directs the Social Development and Well-Being Lab. Dr. Rodman received her Ph.D. in Clinical Psychology from Harvard University and completed her postdoctoral fellowship in the Stress and Development Lab in the Department of Psychology at Harvard University.

She completed her clinical internship at the Boston VA Hospital, rotating through the general mental health clinic and the residential substance abuse treatment program. Dr. Rodman’s work centers on the social interaction of teens, examining how social experiences interact with ongoing cognitive and brain development.

Also joining us will be Dr. Ashley Hagaman, who is an assistant professor in the Department of Social and Behavioral Sciences at the Yale School of Public Health. Dr. Hagaman earned her M.P.H. from Emory University, Rowland School of Public Health, and her Ph.D. in Medical Anthropology from Arizona State University.

She is also a qualitative methodology — methodologist with the Center for Methods and Implementation and Prevention Science and holds a secondary appointment in the Department of Anthropology. Her work focuses on systems-integrated interventions in a global context to address suicide, mental health, and the life course impacts of interpersonal relationships on health and psychosocial well-being.

Also joining us will be Dr. Jane Zhu, who is an assistant associate professor in the Division of General Internal Medicine at Oregon Health and Science University. Dr. Zhu received her M.D. from Harvard Medical School and a master’s degree in public policy from Harvard’s Kennedy School of Government.

She is a core faculty at the Center for Health Systems Effectiveness and an adjunct senior fellow at the Leonard Davis Institute of Health Economics at the University of Pennsylvania. Dr. Zhu’s research centers on healthcare access and quality, particularly for mental and behavioral health services, as well as the effects of provider incentives and organization on healthcare delivery.

So, please help me in welcoming Dr. Silvia Lopez-Guzman to the stage.

SILVIA LOPEZ-GUZMAN: Thank you so much for that introduction. And thank you to the organizers of this event for this invitation. And happy 75th to the NIMH.

So, today I’ve chosen to like move a little bit away from my comfort zone. I’m barely going to touch on my science, and I’m just going to tell you about what makes me, you know, kind of optimistic about our progress towards delivering personalized care in psychiatry.

Let’s see if I can handle this double — no. I guess this. There we go. All right. And so, I’m going to do my best to summarize the evolution of the field’s ideas about individualized psychiatry or personalized psychiatry and the challenges that we’ve come to face.

And then I’m going to pivot to discussing some promising sources of data, which, combined with the novel data analytical methods afforded by machine learning and artificial intelligence, can maybe help us push forward.

And I’m going to mention, just as examples, a couple of promising, individualized interventions that are starting to be used today. And I’m going to end just on some thoughts of where we’re at and what we need to do to get these novel ideas from kind of like the workshop to the implementation and clinical science.

And I’m going to just give a disclaimer that, of course, I’m not going to be talking about research that I’ve done, right? And in some cases, I’m going to be talking about things that I really don’t know much about [laughs]. But I am going to pepper in maybe a little bit of the work that we do in my lab.

Okay. So, of course, you know, this is what we deal with, right? We are interested in trying to answer questions about an individual, right? And the questions, clinically, that are driving us are, can I use information from this individual to reach an accurate diagnosis, to predict and identify how severe the disorder is? What are the risks? What kind of treatment should I select, and how is this person going to do with this intervention?

And so, in the early 2000s, the first efforts of genetic sequencing in individuals with mental health disorders were combined with, you know, the knowledge that there was huge heterogeneity when it came to responses to pharmaceuticals. And so, that sort of, like, propelled the sort of like, field of pharmacogenomics.

But, of course, as you know, while many of these assays currently exist. They haven’t really been widely adopted. And this is in part because some of the studies are not very high quality, not very well powered, and there are concerns from providers that what they might end up doing is just kind of perpetuating or amplifying already existing health disparities.

Later, there was another wave, right, of interest into the search for biomarkers. And I would say that in parallel, there were a lot of efforts in trying to get samples from plasma or CSF or other biological samples and try to investigate what are molecules that could be informative of the presence or absence of a disorder or specificity about a particular disorder.

And in parallel, there was a big push for finding biomarkers using, you know, noninvasive methods like neuroimaging. And — but both of these efforts kind of faced similar constraints of small samples and kind of low reproducibility. And so, clearly, none of these approaches alone have provided kind of implementable tools yet.

And I should say that they have been significant efforts in bridging together genetics and neuroimaging, and we have learned a lot. But we’re not yet at the point that any of these, kind of technologies are recommended for clinical implementation routinely. So, why has it been so hard?

Well, at least in part, I think it is due to kind of like immutable features of mental health, the right conditions, namely, that psychiatric disorders suffer from low essentiality and high heterogeneity. And what this means is that there is no single neurobiological mechanism that maps on to the behaviors that characterize a disorder, right? And this is because the brain-behavior relationship is “degenerate,” right?

There are multiple behaviors that map onto a single neural mechanism. And then there are multiple neural mechanisms that lead the same behavior, right? And furthermore, these relationships are not invariant to external factors, such as social and environmental context, right?

And then in terms of heterogeneity, what heterogeneity means here is not heterogeneity across people, which we know is a factor, but heterogeneity in the sense that all of these explaining factors of the disorders actually interact in pretty complex and seemingly idiosyncratic ways.

So, where’s the solution? Well, at least in part, you know, the solution should be data, right? Because the more factors we measure and we can account for and that we can combine, the more we can account for these complex interrelations. But data is — alone is not enough. And I and others have argued that we also need to collect data over time, right, to capture, you know, kind of instabilities and factors like development.

We also need to know what context the person was in when we collected the data, right? So, a patient comes in, and we’re going to do an fMRI session. We kind of need to know something about what’s going on that day. Because there might be factors that we’re measuring that have very much to do with what happened to that person coming into the lab.

And then the other thing that I think we really need is theory, right? That will help us kind of organize our ideas about what data to collect and in what way. So, let me now shift gears to, you know, a few examples of promising new data approaches that have become more and more common in the last decade or so.

And, you know, one of the first things that I’m going to talk about — and I know that this is going to come up in other presentations — is the fact that now we can use technology to sample, quite with high density, clinical and behavioral data. Here I’m showing you an example of a study following individuals with psychosis and at risk of psychotic disorders and just basically sampling multiple times a day.

There are symptom levels, right? And trying to use machine learning methods to kind of derive different clusters for different types of profiles and make — and base decision making on them.

You can also combine these sort of longitudinal repeated measures approaches with measures of behavior. And so, here, this is from a study that we performed a while ago in individuals with opioid use disorder that were seeking treatment in an outpatient clinic in New York City.

And what we basically did was repeatedly assess both their symptom levels, but also a number of measures of computational measures of decision making, to try and see if what are — what combination of these factors is, in fact, predictive of imminent reuse events. And what we found is that, indeed, what you expect is that a combination of these factors play a role in the prediction.

Digital phenotyping is another approach that we can take using smartphone data or online data. This is from Brenda Curtis’s lab trying to predict outcomes in addiction on the basis of language in social media posts and showing that, in combination with clinical assessments, the prediction of imminent of relapse was improved.

Now, in addition to what we — the kind of data that we can get from smartphones, we have wearable devices. Earlier we heard about applications and uses for wearable devices. This is one example. So, this is trying to predict stressed states on the basis of physiological measures from the sensors with high precision.

We too have tried to combine, again, this with behavior and decision making. And what we’ve been able to show is that measuring things like facial expression and arousal responses and heart rate variability can greatly — and during decision making, can help us classify or extract when someone is in a particular clinical state, from high craving to low craving.

And then moving away from smartphone and wearables, there is a treasure trove of data in electronic medical records and in all the interactions that users have with providers. So, the United States is not really at the forefront of use of electronic medical records in psychiatry. And there are, you know, real difficulties when it comes to what to do with those data because there’s both structured text and unstructured tests.

But this is one example where AI could really be helpful in leveraging that source of data. On the right, I have an example of another way of leveraging the contact between patients and providers. So, this is using machine learning methods during clinical interviews and basically extracting features from, you know, verbal information, nonverbal information, facial expression, and even kinetics, to try to make predictions about group assignments or severity.

And this is really outside of my realm of expertise, but really, there’s been an explosion in the field of multi-omics, like the costs of running assays at different levels, from like genetic expression to proteins and molecules, has really gone down. And so, there is a place in which, you know, much like the 2000’s wave of pharmacogenomics, these can be used in combination with other sources of data to help — to aid in precision medicine.

And this is, you know, kind of one of the last things I’ll talk about, neuroimaging, right? So, I mentioned in the — at the beginning that there was a lot of excitement around neuroimaging and finding differences and signatures of brain disorders and in — that could allow us to separate or differentiate patients from controls.

And what we found — we found some of those differences. Now, the shift has been going in the — not in the direction of comparing patients to controls, but kind of figuring out if there are individual signatures of connectivity, right, circuits or biotypes that actually map on to treatment response and to multiple different disorders, right, and clinical manifestation.

And what we want all this data to do is to help us inform intervention. And so, here I’m showing you a couple of examples of individualized interventions. And so, on the left, I have ecological momentary interventions, right? This is like ecological momentary assessments, but the idea is that there are multiple interventions that are delivered through time, right?

This is — on the left is a study aimed at increasing self-esteem in youth through all these specific tasks that were delivered at different times and showing that these types of interventions can be effective.

And on the right, I’m showing you an example — an array of different — and it’s really invisible, I apologize — an array of different commercially available apps that are currently collecting a lot of information on symptoms, sensor-based information, device-based information, self-report.

But those apps, even though they purport to be, you know, for mental health — and there are some studies that show that using those can be beneficial — they don’t really deliver any type of intervention. And that — and if they do, they don’t tether the information to the state that they can predict that the patient is in, right?

And so, this is the idea behind just-in-time adaptive interventions, which is that we could use, you know, kind of a closed-loop approach to figuring out how to deliver the intervention in the moment that it’s needed. Okay. So, now, we have a much more full picture and complex picture of what we might need.

And during the last minute, I’m just going to try to reflect on what it’s going to take to go from these exciting new ideas to something that is implementable. And the truth is that, you know, only about, you know, less than half of a percentage of, you know, transdiagnostic models, computational models, prediction models, machine learning models, right, are actually implemented in clinical practice.

And the reason is because we haven’t done the validation studies yet. We’re not — they’re not sufficiently replicated. So, there’s a lot of work to do in that space, and there’s multiple challenges ahead. I’m not an expert on this, and I think others will touch on it. But there are — there’s, of course, very complicated ethical issues around the use of AI and machine learning in precision medicine.

Just because we can collect the data; should we collect the data, how are we going to protect the data, is something that is really important. We need to restore kind of this idea of personhood and context and culture and let that inform how we do our studies. And this, you know, has been talked about a lot in the morning about how to involve stakeholders and, you know, kind of like have these looping effects of community-based, informed research.

And finally, we need to figure out ways to lower barriers for clinicians. It’s not always easy, even if you want to, to implement these technologies. And so, that — there’s a lot of promise in future efforts to do that. And with that, I’m just going to end. And thank you for your attention.

ALEXANDRA RODMAN: Hello. All right. Thank you so much for having me. It’s been thrilling to hear from the rest of you. So, what I’d like to talk to you about today is Coming of Age in a Digital World: Advancing Smartphone Measurement to Predict Adolescent Mental Health.

And so, this is me. Adolescence, as I’m sure you’re all well aware and remember, is a time when so much is changing in the brain, physically, psychologically, and of course, socially. And in addition to taking on new roles and experiences, adolescents are notoriously preoccupied with peer approval and social belonging. And every interaction can feel more intense, whether it’s the excitement of a school dance or the sting of being turned down by your crush.

So, back to 13-year-old me. This picture is actually from a group photo shoot for my friend’s birthday. And this memory is so incredibly strong. You’ll see the limited [unintelligible]. That was — that’s real. This memory is incredibly strong. Because I remember feeling like this friend group was locked in, right? Like we had done a professional photo shoot. And we were going to be best friends forever. And that felt really, really good.

But little did I know that some of these ties wouldn’t last, and the falling out would be pretty painful and all-consuming. Typical adolescents, right? But why is that? What is it about adolescence that makes social experiences so intense? And on some level, it has to do with how we process social information.

Just like any other kind of information, we don’t just absorb social information as a one-to-one, input-output process. Instead, the information we perceive is filtered through our own individualized lenses and is subject to distortion or bias due to prior expectations, motivations, and interpretations.

So, when it comes to having varied social experiences that range from positive to negative, like being invited to a party, feeling left out, the way we process those experiences may take different forms. And positive and negative experiences could be weighted differently. And this weighting matters because the biased information is then integrated into more global impressions of how we view ourselves, others, and the environment, guiding our expectations going forward.

So, in my work, I take a developmental perspective and focus on the age-related differences in social processing behavior and experiences to try to understand adolescents’ unique social sensitivity and what happens when things go awry.

The transition from childhood to adolescence, typically occurring around age 12, is often described as a period of social reorientation. Adolescents spend less time with their families and more time with peers. Social belonging becomes increasingly important, where teens are more dependent on each other for support. And meanwhile, social groups are in flux during this time, subjecting adolescents to greater frequency of peer rejection.

This reorientation is accompanied by enhanced intensity of social experiences that can shape emotions and behaviors in meaningful ways. Adolescents are more preoccupied by peer approval and show more intense emotion and stress responses following peer rejection. And while rejection is especially common during this time, peer rejection and a history of it has been linked to depression.

Indeed, most adolescent mental health problems emerge in the aftermath of interpersonal stressors, such as being bullied, a romantic breakup, or peer conflict. And at the same time, adolescence is a period of peak risk for the emergence of mental health problems, particularly depression, anxiety, and suicidal behaviors.

At the start of adolescence, the prevalence of mental health disorders is at about 1 to 2 percent. But by the end, this increases to 25 to 3 percent. In fact, 75 percent of all mental health disorders will emerge during the adolescent years. And this sharp rise in mental illness spans many disorders, with the average age of developing any mental illness falling around 15 years old.

Importantly, onset at this time tends to have a more severe and lasting prognosis into adulthood. So, with all this in mind, clinical and developmental psychologists think of adolescence as a period of vulnerability, when social sensitivity comes at the same time for — the same time as risk for mental health problems.

And while I’ve pointed out the clinical risks associated with this period, there’s also tremendous opportunity. Adolescence is when clinical interventions stand to make the biggest impact, ultimately shifting trajectories of risk.

This is due in part to widespread changes in brain structure and function, where the developing brain is making and pruning connections based on life experience. And these ongoing changes contribute to the social sensitivity and clinical risk we see during adolescence.

But at the same time, these changes support dramatic growth and learning. And this enhanced neuroplasticity, when the brain is particularly responsive to the environment, provides, again, a window of opportunity where interventions can make the greatest impact, especially when compared to adulthood, when most people first seek treatment for mental health problems.

And given the substantial change that occurs in the domains of social experience, brain development, and risk for mental health problems, my lab’s work centers on the interplay of these domains, studying how social experiences interact with ongoing cognitive and brain development to shape adolescent well-being and clinical risks. Sorry.

Our primary questions explore what makes adolescents uniquely sensitive to social experiences, how social factors function as mechanisms of risk for psychopathology, and which factors enhance resilience against mental health problems?

And to answer these questions, we take a multimodal approach, including experimental and observational approaches, using novel behavioral tasks, fMRI neuroimaging, and digital phenotyping via mobile phones.

And while adolescence has always been known as a period of immense change, what that looks like today is rapidly evolving due to the sudden omnipresence of the digital world. Soon enough, teens’ real worlds and digital worlds will become fully integrated, if they haven’t already. So, it’s critical that we begin to study adolescents in new ways that fully grasp the complexity of the adolescent experience.

And so, for today, I’m not going to talk so much about my brain research, though I love it. And of course, we aim to integrate it with our real-world measures. Instead, I’m going to focus on our work using experimental tasks to probe adolescent sensitivity to social experiences, followed by our past and current work examining smartphone use and its direct and indirect associations with stress, mood, and anxiety.

So, first, I’d like to share some work investigating the social motivation and learning processes that may render adolescents uniquely vulnerable to peer stressors. In a study of 102 participants, aged 12 to 23, we use a physical effort paradigm to see how hard adolescents were willing to work to find out if they were liked by their peers.

And in this figure, I show you their expectations of being liked on the X axis and how hard they squeezed to obtain peer feedback on the Y axis. And as you can see, adolescents squeezed harder than adults overall but worked hardest when they thought they’d be more strongly liked or disliked, working the least for expected neutral feedback. Adults, on the other hand, worked harder the more they expected to be liked. And next, we were interested to find out what adolescents and adults did with that feedback once they received it.

In a study of 107 participants, aged 10 to 23, we asked how peer acceptance and rejection impacted self-esteem. On the Y axis is age and — I’m sorry, on the X axis is age, and on the Y axis is change in self-esteem from before to after the task. We found that after receiving the same amount of positive and negative feedback, teens showed a drop in self-esteem, while adults showed a curious boost in self-esteem.

So, across both studies, adults show a self-protective response, whereas teens valued strong signals of inclusion and exclusion, even though their self-esteem is particularly impacted by it. And next, I became interested in investigating social behaviors as a mechanism of risk.

And in this next study, we focused on phone call behaviors. Here, we took a within-person approach, examining how monthly fluctuations in these behaviors explain the relationship between stressful life events and anxiety symptoms over the course of a year in 30 adolescent girls. We found that when individuals experienced more stress than usual, they also engaged in more phone calls than usual.

But what we found next was surprising. We found that more incoming phone calls in turn related to greater anxiety symptoms the following month. Moreover, calls mediated 40 percent of this stress-anxiety relationship. And this was the kind of study that we love and hate [laughs] that just left me with more questions than I started out with.

I had expected that calls would help mitigate the negative effect of stress on anxiety; reasoning that, calls signaled social support. But our results showed the opposite, which turned out to be a blessing. I wondered, “What were these calls? Was it the stress itself? Who were they with?” And in the end, it really impressed upon me the importance of getting more granular data.

So, we started to scratch the surface of this in a study examining social factors that enhanced resilience. During the COVID-19 pandemic and a longitudinal sample of about 250 children and adults, we found that the relationship between COVID-related stress and depression and anxiety symptoms, or internalizing symptoms, six months later, was positive — positively related in youth, who decreased or showed no change in how much they socialized over digital platforms during the stay-at-home orders.

But for those who increased socializing over digital platforms, this relationship was effectively erased. And we found that this effect was primarily driven by phone calls compared to other digital means of socializing. And in a recent preliminary study of nearly 30 adolescents followed monthly for up to a year, we not only examined different types of phone use, like communication, social media, gaming, entertainment, but we also examined different metrics of phone use, like screen time, pickups, notifications, all of which had differential associations with positive and negative mood.

And importantly, we did not find that oft-touted relationship between overall phone use and negative mood. We found actually a very small positive effect. And the primary takeaway here — and I know I’m not going into a ton of detail — is that — I would say the primary takeaway is that this is a nuanced picture where different types of phone use likely serve different purposes. And we need to start measuring and analyzing phone use in a way that adequately captures the complexity of the behavior. And some methodological advances in recent years are finally allowing us to do just that.

So, to that end, I’m thrilled to tell you a bit about some upcoming work. We’re currently launching our first intensive longitudinal study, co-designed with a teen advisory council, where 80 teens will complete eight monthly visits to gather intensive social and emotional functioning data. They’ll come in for a lab visit day, where they’ll complete several behavioral and fMRI tasks.

We’ll also conduct ecological momentary assessments or brief surveys pinged to their phones and several week-long bursts to ask about emotions, behaviors in real time as they make their way through their day-to-day lives. And finally, we’ll continuously and passively collect mobile phone sensor data, including GPS, call and text logs, activity, physiological data from smart watches.

I’m also happy to talk about the ways in which we’ve designed our recruitment and data collection processes to increase feasibility, access, and representation. I’m also excited to share that this R00 has allowed me to pilot a collaboration with computer scientist Varun Mishra.

Together, we hope to advance smartphone measurement by pairing objective smartphone data with qualitative reports of the nature and function of smartphone use in real time. So, as smartphone time series are coming in, an adaptive machine learning algorithm will consider these patterns and contextual factors to identify anomalous patterns of activity, which have been found to be predictive of negative outcomes.

And this will then trigger an EMA survey to ask participants about this anomalous event; who was it with, what was the purpose, the function, how they felt. And this design helps us move past some of the early barriers to progress by using objective measures instead of self-reported estimates, focusing on within-person effects instead of individual differences, and deep phenotyping by tagging objective smartphone data with this descriptive information, all the while we get these perspective bidirectional relationships at multiple timescales.

And so, we believe this level of granularity will be critical to advancing measurement of smartphone use, that, in turn, is associated with well-being, ultimately predicting when adolescents are most at risk for negative mental health states, leveraging data-driven approaches to enhancing resilience when they need it most. So, thank you, Silvia, for teeing me up. Not for nothing, we’ll be submitting this R01 proposal soon. So, wish us luck and stay tuned. Thank you very much. [laughs]

ASHLEY HAGAMAN: Oh, boy, I’m going to start talking about places where there are no smartphones. So, buckle up.

[laughter]

Thank you so much for the opportunity to speak at this event with so many other inspiring and amazing researchers. My name is Ashley Hagaman. I’ll be sharing with you today some of the pragmatic innovations that we are bringing into the future of suicide prevention research around the world.

I work with so many amazing Pakistani and Nepali scholars and doctors. And I wish I could introduce you to every single one of them, but I can’t. So, here they are, and none of this happens without them.

So, to begin, more than 700,000 people die by suicide every year. Even larger, 16 million people attempt suicide every year. This doesn’t account for the families and the friends and the social networks that endure the rippling effects of those acts. Importantly, up to 75 percent of those deaths happen in low- and middle-income countries, or LMICs.

In LMIC settings, 1 out of 10 people that need mental health care, only one will receive it. This disparity is magnitudes larger than the important disparities that we have here in the United States. However, despite the disproportionate burden of suicide in LMIC, our knowledge and interventions are heavily anchored on western theories.

Our amazing librarian at Yale did a search for us, and last week found that, crudely, 11 percent of suicide research is conducted in LMIC. And based on the evidence we do have, we know that risk and recovery profiles differ across culture and context, which is why we see a lot of global variation in suicide rates. So, there’s incredible disparity in burden and science.

And the last thing I’ll say about suicide, at least more broadly, is that in Southeast Asia, where I work, there are far more female suicide deaths than in any other region of the world. And it’s an important outlier and one that we try to address in our research programs.

I want to say a few things about my own lived experiences and motivations. I was trained as an anthropologist. And yes, you’re about to hear about a lot of clinical trials from an anthropologist, so also buckle up.

[laughter]

A part of that means that I get to live and learn from families while I do my field work. I have learned so much about maternal mental health, about family, and about care systems from the mothers that I got to live with. I studied suicide. I studied loss and complex notions of agency around mental health, and I got to do it alongside what became family. And I afford a lot of my own career to these amazing women that housed me for years in Nepal.

And as I became a professor and a principal investigator, I also became a mother. And I suffered a lot of personal suicidal loss and challenges within my own social networks. And a part of what makes my job the absolute best is getting to do it alongside these amazing, strong, and seriously smart women, mothers, and scholars.

And so, one of the things that my future and suicide prevention research is defined by is my ability to amplify the amazing commitment, tenacity, and bold work that these women lead. So, I want to start my talk off with dedicating it to them and say how excited I am to be a part of advancing suicide research with them in the coming decades.

And so, my talk is about the future of suicide prevention work. And I hope that you see it in the bold women and youth that are leading it and what it’s looking like in some of the corners that we work in Nepal and Pakistan. So, naturally, as someone that does research in places that I do not call my own home, it’s hard for me to answer what that future looks like in 25 years.

And so, I asked [laughs] our community advisory boards, our youth advisory boards, my colleagues, and communities what they thought that should look like. And they want their own cultures and explanatory models to become pivotal parts of suicidal theory. They want people to feel like they can disclose their thoughts without harm. They want local experts and local leaders.

And I’m so happy to say that our trials, the ones that NIMH is funding, are doing all of these things. We’re creating local leaders. We’re creating community-driven interventions using local theories. And I’m so proud that the women that were researchers a decade ago with me are now finishing their Ph.D.’s and are named co-investigators on the trials that we’re now running.

So, that, to me, is one of the most important things that the future of our research can do. It can put in positions of power those that have been most neglected from the research. So, we’re making it happen. And a part of what makes it happen is grounding all of our co-design and clinical trial work in lived experience advisor reports [laughs].

Thank you, Dr. Bellamy, and everyone else who has really highlighted this point. I think if you get a main theme, this is probably it. And so, they really guide all of our processes and procedures. Our team see that the feature of this work is anchored in culture and context and how to implement. The individual is so important and so is their community and the systems and the policies and the structures that they exist within.

So, for example, in Pakistan, suicide attempt was only decriminalized less than two years ago. So, prior attempts were punishable by imprisonment and fines. So, we cannot build a suicide intervention or ask people about their suicidality without considering and attending to the legacies of these policies. I have lots of other examples here.

But a part of our strength as anthropologists and an interdisciplinary team is that every part of the work that we do considers these elements to optimize our interventions efficacy and likelihood of success. So, one of the ways that we’ve done this is to develop indigenous theories of suicide, led, of course, by our indigenous scholars. And so, these grounded theories become the foundation of our intervention and implementation work.

And so, I’ll give you one quick example, hot off the press — and like everything is hot off the press because all of this work is in progress — from work that’s led by Gul Saeed and Sidra Mumtaz in Pakistan. And we sought to understand how women think and talk about a life worth living and what transitioned them from suicidal thoughts to attempts.

And so, one part of that theory — I won’t explain the whole thing [laughs]. You can read the paper. It really focuses on how women long for sabr and sukoon, patience and peace. These are states that women describe having strength and control. So, we attend to this in both our measurement of suicidality and management of suicidality.

And there’s lots of other examples that are coming out soon from Renu Shakya and Kripa Sigdel from our work in Nepal. I’m going to walk you through the next four years of research trials that my lab is running in Nepal and Pakistan. Importantly, these are only — these are the only [laughs] suicide prevention trials at the community and primary care levels that have ever happened in either of these countries.

So, they are important reasons why they’re pilots. They’re developmental, and mostly that they’re carefully co-designed and measured. And so, we create packages of suicide prevention programs and design these to be deployed in various settings. We’ve done it in a large Nepali hospital system. We’re currently running pilot clinical trials in the primary healthcare system in rural Nepal and for youth in a community in Nepal and for mothers in Pakistan.

And we designed these complex interventions and their implementation protocols by intervening on the individual at risk, but also intervening on the families and the clinicians and the systems that they’re a part of. So, in this way, we’re doing what we call hybrid trials, where we study both how effective the intervention is on the individual at risk for suicide and how implementable and potentially scalable and sustainable it is in the real world.

So, we study clinicians and the peers that are delivering the intervention in the systems that they work and live. So, what’s in the package? It’s been deconstructed and reconstructed from several brief interventions shown to have evidence base for addressing suicide, at least in the west.

Some of these elements are from the Zero Suicide approach in western health systems. Some are from the Mental Health Gap Action Program, which is a program that equips primary care physicians to detect and treat common mental disorders, including suicide. And there are three basic elements.

The first is screening. And we can’t think about screening without thinking about the risks and benefits that someone has in disclosing suicide risk. So, we developed systematic, structured screening tools, including both psychometric screeners and strategies for identifying risk at the community level, which is what we call community-informed detection.

And we’re validating these instruments and ensuring safety for disclosure. We also leverage evidence-based practice of safety planning or crisis planning, but we’ve completely reconstructed it to make sense in Nepal and Pakistan. And I’ll show you how.

And finally, there’s evidence that basic connection and contact addresses important elements of suicidal risk. And we pair this with ongoing support for the person’s preferred care-seeking pathways to ensure that they’re supported in ways that they want to be over time.

The first trial just finished a couple months ago. This was the original development of the suicide prevention package and the design of an implementation in a Nepali hospital. And it’s a really nice example of how we thought about identifying someone at risk and how to support them in the next steps.

This is the emergency department that housed the project. It’s generally super chaotic. And you can see this is like a really not chaotic day, by the way [laughs]. But you can see that families surround patients almost at all times. And that’s really typical in clinical encounters. It’s actually required in the Nepali health system that you have an accompanying family member with you at all times. Because they have to go buy the IVs. They have to go buy the medicines, and they have to bring everything to you.

And so, it’s important to understand what screening would actually look like in this context. And our community advisory board was given all of the screening [laughs] tools and strategies that we could find to identify suicide risk. And they went through all of them, and they picked the one that they thought was most appropriate and then we heavily culturally adapted it.

We did this in all of the settings. Here, they chose to ask suicide screen, which was developed by Lisa Horowitz and colleagues. And this is what the clinical workflow of the screening tool looked like. The most important part was training of staff for how to introduce the questions, especially given suicide really isn’t ever discussed in biomedical care settings.

And so, our CAB and clinicians work together to develop the script to introduce the questions that were coming, why [laughs] they were being asked these questions, and then what might happen in order to optimize their comfort in disclosing. So, our CAB helped co-develop the workflows and implementation blueprint and train the clinicians and like all — with them all along the way.

Briefly, some of the outcomes of that initial screening, 14 percent screened positive, which is higher than what we see in most U.S. hospitals. And around 2 percent were at really high risk, meaning they had active thoughts and plans for doing suicide in the immediate future. That’s about probably the same as the U.S.

We embedded a validation study into the psychometric analysis of the tool, suggested that it’s reliable. Our qualitative work uncovered some really important implementation distinctions from the western settings. I won’t go through all of them. But to give you a quick flavor, the ASQ toolkit says that a screen takes less than 20 seconds, which, like, if you role-play it, it can.

But this is really different in Nepal, where folks are far less conditioned to answer serious questions about death with a one-word answer. And so, staff needed time to listen to stories, whether someone was positive or negative. And so, again, we need these really important implementation strategies to make this work.

So, once we know that someone might be at risk or that they’ve had a recent attempt, safety planning is a really effective way to help them and their support networks know that there’s always something they can do to keep them safe.

In the U.S., you can see that these plans are really homeworky. They’re quite structured. And they rely on handwriting and literacy. In Nepal and Pakistan, it’s common that folks cannot read or write at all. So, we wanted to, again, think of deconstructing and decolonizing these tools to make them implementable and useful.

And the last thing that I’ll say about safety planning in general is that we don’t really know the mechanisms by which it works. We think it works differently for different people. So, a part of what we’re doing — and we know it might work for an individual. But it also works for families. And it also works for the treating clinician or the provider. But we don’t really measure how those work and how effective it is for each of those individuals.

So, that’s a part of what we’re doing in some of these trials that are coming up. So, in another clinical trial that NIMH just funded a few months ago, we’re enhancing the already existing mhGAP package of strategies that I talked about earlier for responding to suicide so that primary care physicians — they’ve already been trained in it, but they’re not doing it.

So, the whole clinical trial is to figure out how do we get them to do it better with more support. So, what does safety planning look like with some of our illiterate populations? First, we don’t call it a safety plan. We call it an ashako diyo, which literally means light and hope, which is really beautiful way, I think, to think about what this instrument can do. But also, it’s not quite so awkward, like a safety plan.

Second, we worked with indigenous artists to create stickers that visualized various components of the plan, so it doesn’t rely on writing and reading. You can see some of the stickers that are here. The pocket card with those visuals helps both the person that’s facilitating the safety planning and the person that’s receiving the safety planning sort of understand what’s going on and what they’re working on together.

And we task shift a lot of the work that physicians were originally tasked with in the original mhGAP protocol to community health workers. So, the original mhGAP protocol says that the primary care physician should follow up with the patient every two weeks. That is completely infeasible in many of the contexts that we work. And so, we get community health workers rather to do those visits at the patient’s home themselves.

And so, we’ll measure how it worked, both with the high-risk patients that we enroll in our trial and with the clinicians to see how well and effective and with what quality they can implement it.

We also got funds two months ago [laughs] from NIMH to develop a community-based peer package for youth suicide in rural Nepal. And so, the trial has similar elements, but our youth advisory board, who all has lived experience with suicide, and our partner, SOCHAI, which is a women-led social change organization that’s been pioneering innovations for public health all over Nepal, are adapting the package.

And they’re thinking about ways to make the plan into indigenous jewelry or songs or other materials that don’t rely on something that is written. Another key part of the trial is that it’s protocolizing helping first families when they have a youth in their household who’s at risk and then also figuring out how and when to engage them.

So, this is one example of how NIH is funding and supporting innovative futures and research because two of the named co-investigators on this project are experts by experience. So, they don’t have Ph.D.’s or M.D.s, but they have incredible and irreplaceable expertise to make the work succeed.

And the last trial I’ll tell you about is our suicide prevention package designed by women for women, delivered by peer mothers in rural Pakistan. It’s another hybrid type 2. So, that means we’re studying both how effective it is on the suicidal mothers and how well the peers can implement it and make it sustainable within their health system.

It’s called the Khushal Pur Ameed Zindagi Trial, which means happy, hopeful life. And our CAB with lived experience picked a different screening tool, the patient safety screen, and developed scripts for patients and the families. There’s like a whole family engagement part of the intervention because it’s just so necessary and work like this.

And really cool, we designed new tools to measure suicide severity that are anchored in the cognitions, emotions, and moralities that are wrapped up in how individuals think about suicide. So, you have to stay tuned for all those tools and measures and validation papers that are quickly coming.

Just really quickly, the safety planning looks really different. Again, in Pakistan, it’s actually anchored in a narrative story approach, where we have a visual story of a woman named Shu Gupta, who’s a mom, who, you know, wrestles with her own suicidal thoughts and behaviors. And it’s a really effective way of engaging someone in safety planning and sort of this safe but kind of indigenous way of knowing and learning way.

I want to say a few things about how we’re advancing methods. We’re developing new measures to quantify suicide severity and mechanisms of intervention action. We’re developing systematic measurement strategies to assess fidelity and quality that primary care physicians and peers deliver in their evidence-based practices.

We thought a lot about models of supportive supervision to support task shifting suicide prevention work to peers so that they’re confident, safe, and cared for. Every single person involved in our project in any way receives free mental health care, hands down.

The last thing I’ll say is really about the persistent challenges, I think, especially doing work in low- and middle-income settings, that we face in a funding system that’s really full of inequities and limitations.

The first is that the future of innovation depends on recognizing diverse kinds of knowledge and expertise. And NIH is doing this, and we can’t be more excited.

We need to design reimbursement structures that are anchored in social justice and attentive to inequity. Rural partners don’t have social capital to pay rent or salaries for months on end, waiting reimbursement. Our implementing — or capital just doesn’t exist in rural areas.

One of the starkest inequities and realities that our partners face is really limited indirect rates to keep the lights on and pay for key administrative services. There’s an incredible amount of hidden curriculum and grant systems and legal requirements.

And it’s — another thing that NIH is supporting, through one of the capacity-building arms in one of our trials, is to actually create a training system between Yale and our local partners to submit and support the highest quality and most innovative research we can. And would I really be a researcher if I didn’t ask for more money?

[laughter]

In reality, we’re working in context where, default, there’s three or five languages. And we can’t just have an English version and an Urdu version. We need multiple versions of all of these things. And we never have the capacity to do that.

So, there’s just some of the things that we wanted to highlight to continue to build equity in the future of mental health innovation. So, thank you so much. I’m so grateful to have this opportunity and for our partners that make this work possible.

JANE ZHU: All right. Is lunch hitting everyone? Because if it is, please feel free to stretch and stand up. My name is Jane Zhu. I really appreciate the opportunity to be here today with you all.

So, you know, this morning, we heard a lot of amazing presentations about the forefront of science, new treatment modalities, precision medicine. But I’m a primary care physician. And the sad reality is that I can’t even get my sickest patients in to see a psychiatrist with the current availability of medicine that is existing.

So, you know, we’ve reached an all-time low in uninsurance in the U.S., and yet, everyone in this, you know, room knows that access to coverage, access to — or availability of these treatment modalities has not translated into access to care. And so, that’s what I’m going to be talking about a little today.

So, it turns out that people with the same insurance experience vastly different utilization and mental health outcomes. And so, when we look at mental health utilization rates in Medicaid, for example, the largest single payer of mental health services in the U.S., we find an eightfold difference in the highest versus lowest used areas in the country.

So, I think this figure raises some interesting questions. Why is it, for example, that Duluth, Minnesota, is an outlier in outpatient and emergency visit rates for mental health duress? Or is this an area with high healthcare capacity but relatively low quality of care?

Similarly, what explains relatively low emergency room use and above-average outpatient mental health use in Texarkana, Arkansas? Is this an area that’s appropriately shifted its resources to the outpatient setting, or is this an area with relatively mild to moderate mental health conditions, as opposed to severe mental illness?

The answers to these questions are yet unknown. But by studying enrollees who move from one region to another, researchers have actually been able to disentangle some of the factors contributing to this variation. And they’ve attributed about 60 percent of variation in healthcare use to place-specific factors. So, these are things like provider supply, regional organization, systems of care, as opposed to patient- or individual-specific factors like personal health risks and preferences.

One of the place-specific factors which I study and which I believe to be understudied is this role of state policies and insurance design, particularly through managed healthcare. Managed care is a health insurance approach that is now the dominant form of healthcare delivery and financing in the U.S.

And importantly, managed care organizations seek to control costs and ensure quality of care through various levers that intersect with market and state political and regulatory environments, state procurement processes, and managed care plan structures like profit status.

These functions that managed care organizations perform might include utilization and clinical management, so monitoring covered services and use, including prior authorization, other gatekeeping measures, establishing provider reimbursement rates and payment procedures, and contracting with select groups of providers — provider networks that deliver care to plan enrollees.

And so, I’m going to be focusing on one of these functions just to illustrate the importance of this to patients. So, when we look at networks of psychiatrists across healthcare markets, we find that these networks typically contain low shares of psychiatrists that are available in a given service area.

On average, across Medicare Advantage, Medicaid managed care, and the ACA individual marketplaces, we find that about half of these networks include fewer than 25 percent of all available psychiatrists in a given service area. Further, psychiatrist networks are consistently narrower than those for primary care physicians and all other specialties.

Let’s zoom in further from the network level to the provider level. And we get a sense of how these in-network providers are actually distributing their services. Most dermatologists, as you can see in the top here, are seeing small volumes of Medicaid patients. But it’s fairly distributed on that low end.

If you’re a primary care physician like myself, you’re seeing a pretty even case mix across these insurance types. And if you’re a mental health provider, there’s almost a bimodal distribution between people who see zero Medicaid patients and people who see almost all Medicaid patients.

So, one important implication here is that not only are we seeing narrow networks of providers to begin with, but even smaller sets of core providers are delivering a disproportionate share of mental health services, particularly in Medicaid.

Let’s zoom in further to see what the patients experience. Managed care plans are mandated to provide transparent information about who’s included in network for their plans. And if you’re, you know, shopping around for health plans. For example, many of you may have used these provider directories to choose your providers to select for plans.

And so, we compared consumer-facing provider directories to administrative claims data in Medicaid managed care. And what we find is quite jarring. More than two thirds of mental health prescribers — so, psychiatrists and psychiatric mental health nurse practitioners — and more than half of psychotherapists that plans list as a network, are in fact ghost providers who don’t care for these patients at all.

These findings in aggregate have been replicated in other insurance markets beyond Medicaid confirming that patients in reality are facing an ever-narrowing funnel of available providers that they can actually access. There are, of course, important push and pull factors that contribute to the narrowness of these networks.

From the perspective of managed care plans, broader networks on the one hand, provide important patient goals like provider choice and expanded access to providers. Some states may have also any-willing-provider laws, which require insurers to accept any provider in their healthcare plan that wants to, limiting the extent to which they can exert control over their provider networks.

On the other hand, insurers might argue that narrow networks can be used to direct patients to clinicians or facilities that are known to be higher performing or higher value. Narrow networks give insurance plans bargaining power to lower provider prices. And on average, plans with narrower networks perform better financially than those with broader networks.

There’s also, of course, important supply side push factors that contribute to low network participation among providers and contribute further to this problem. These factors include, obviously, significant reimbursement disparities, both between mental health services and compared to physical surgical services and across insurance markets and provider types.

Billing delays and other administrative barriers, including those associated with network contracting, credentialing claims processing. And clinical complexity and work environment factors that are often more favorable outside of insurance systems.

Importantly, mental health professionals have also had a longstanding and viable alternative to insurance participation in the form of a robust cash pay market. And in fact, shares of total healthcare encounters, as well as physician-level revenue, have increased in time for private pay amongst psychiatrists compared to, for example, primary care providers.

And the existence of these markets is advantageous in many ways to providers, further disincentivizing providers from participating in insurance. Ultimately, the summation of these factors are mental health networks that are wholly inadequate and exert real effects on patients that have insurance.

So, we see higher out-of-network use and out-of-pocket costs. We see that they have limited access to higher quality providers and team-based care, reduced healthcare utilization overall, and treatment delays and foregone care altogether.

So, the very real impact of this problem highlights the need for future research. And I just wanted to, you know, bring up the fact that these place-specific factors have traditionally been understudied particularly around state policies and managed care design and how they influence how patients navigate the healthcare care system and what this means for their health outcomes.

We need to understand which supply side factors can be leveraged meaningfully by these organizations, by states, to right-size networks with the right services to meet local population needs. And so, for me, a number of really, really simple questions remain, but have yet been unanswered.

The first is the extent to which unmet mental health needs in the U.S. are driven by an aggregate shortage of mental health providers versus — as I’ve discussed today — potential misallocation of providers that exist either through, for example, managed care network design and low insurance participation among providers.

Second, we don’t know to what extent these providers are substitutable and what services and provider types should be targeted to which populations. Understanding how we can better allocate treatment resources across the existing workforce, obviously requires a different set of policy responses than expanding the behavioral health workforce in the longer term.

And third, policymakers have thus far prioritized a number of interventions under the premise that a set of modest incentives will induce provider change, whether it’s, you know, where they’re practicing, whether they’re accepting insurance or, you know, who they’re taking care of.

But these interventions really need comprehensive and robust evaluation to understand which programs, which policies can consistently improve workforce capacity as it exists.

So, I’d like to end with a brief example of the research opportunities that exist in this sphere. Local — so, low reimbursement rates in Medicaid, particularly in mental health services, has been widely accepted as a major factor contributing to provider shortages and reluctance to accept insurance.

We found that Medicaid pays on average 80 percent of Medicare rates for psychiatric services with wide variation in payment across states. But given the unique constraints of the mental healthcare system, we’re not sure to what extent rate increases can induce changes in behavior.

And there’s no empirical evidence that suggests this whether they incentivize new providers to come into Medicaid or they better sustain core providers that already serve these populations. And what magnitude of rate increases are really needed from a policy perspective.

But of course, as we would expect, policy changes move faster than evidence generation can keep up. And so, as of 2024, for example, 26 states have implemented rate changes for behavioral health services as a way to acutely improve access to behavioral health care.

And these rate changes really range. They range from across the board, a whole magnitude increases for all providers to targeted rate increases for select services or provider types.

And this provides a real opportunity to leverage natural experiments in the real world. As those of us who work in Medicaid have heard, “One Medicaid program is one Medicaid program. One MCO, or managed care organization, is one managed care organization.” These are really laboratories from which we can learn a lot about policies.

And then against a relative dearth of evidence that currently exists, future research should really prioritize timeliness and dissemination of data that policymakers need to prioritize which policies yield the greatest effects. Or as an alternative, to reallocate resources away from efforts that aren’t very effective.

And finally, to conduct this research as a researcher, I’m very grateful that we actually have unprecedented access to data. And the data sources that I use and appreciate the most are National Medicaid Claims Data, which is a huge resource. But we should be strengthening our evidence generation with innovative linkages to new sources of data that are, in my opinion, relatively underexplored.

And so, these might include web-based, consumer facing directories, patient surveys, qualitative data, and commercial and proprietary databases which will give us more comprehensive understanding of the patient experience.

So, I’ll end here. Thank you so much to NIMH for the opportunity to chat today and to all of my collaborators and mentors and co-authors and other funders. And thank you so much.

SERENA CHU: So, thank you, Dr. Zhu. Now I’d like to welcome back to this stage all our speakers, so we can have a moderated discussion and questions from our live and virtual audience. So, if you have a question, please make your way to the microphone.

JON COOPER: Good afternoon. My name is Jon Cooper, and I am director of health and wellness for a public school district in Delaware. I have a question about whether any of the research that’s being done has implications for future differential diagnosis of disorders on the slide that I really liked with the low essentiality. I forget what the other term was. But that really struck me.

And I guess I just wonder if at this point there’s a feeling like, “Well, you don’t feel good, so we’re going to help you.” Versus, “You have this, you have this, you have this.”

SILVIA LOPEZ-GUZMAN: I’m not sure that we’re — I think we’ve moved away from the idea that, you know, we’re going to fully commit to the taxonomy that exists. I also don’t think that we’re on the other end. Right?

And I think it doesn’t make sense to be fully on the other end until we fully figure out a better mapping of neural and, you know, biological mechanisms of mental health disorders and the way in which those interact with the environment, with culture, with social factors, with development, all the things we’ve said. So, I guess to answer your question, I wouldn’t say no. We’re not there yet, and I don’t think we should be.

JON COOPER: Thank you.

SERENA CHU: Oh, okay. Other questions?

FEMALE SPEAKER: Hello, everyone. You know, really wonderful panel of presentations. And while I was watching — I didn’t get to see everyone’s but for most — the question in my mind was policy impact and sort of long term. And it was almost like, Dr. Zhu, you read my mind. Because you had really cleanly pointed out specific areas where you can build into that policy work.

And so, I would like to hear just from everyone, your considerations — and even, I think, Dr. Hagaman especially in your presentation, in the very beginning, you pointed out how it was just in 2022, the decriminalization of suicide in Bangladesh. And this is a popular issue in other countries.

So, how do you see — how do folks see their work impacting policy eventually? And/or how are you trying to incorporate that into your research right now? Are you conducting stakeholder involvement or consultations or conducting trainings with people in government or related policy work to create that change later on? Or do you not see connected at all?

ASHLEY HAGAMAN: Is this on? Okay [laughs]. So, I mean, policy in every context is so different. And so, in a place like Nepal, policy is actually determined at, like, the local city level. Like the equivalent to what would be our counties.

And so, so much of the advocacy actually that’s built into our research programs are having to create municipal advocacy structures. And the youth program I was talking to you about, someone from our youth advisory board sits on the municipal government as, like, the youth advocate.

And so, we’ve built that in into a lot of the ways that we’ve been working with our stakeholders and thinking about how we make sure that it’s woven into some of the systems that we work.

Other policies already exist, and a lot of our work — Nepal is, like, so wonderful at creating policies for lots of things. And so, a lot of our work is to figure out how do we get that implemented?

So, how do we get every primary care physician well trained in suicide detection and response? And how do we do that with care and quality? So, I think we also think about, like, how are we helping the policies that already exist get deployed in meaningful ways?

SERENA CHU: Did — Dr. Zhu?

JANE ZHU: Sure. So, I think that policy is where research should end and begin, but that’s a personal bias. Because there’s a lot of great research that’s out there, and it doesn’t get implemented in practice.

And if you talk to policymakers, a lot of them are operating blindly. There are policies that are implemented that are not based on evidence. There are policies that are implemented that are never evaluated for their efficacy, and there’s no outcomes or accountability.

And so, from my perspective, mental health care is so deeply ingrained in the systems in which we practice that it is really hard to produce research without that going to the end user. Which, for me, my research is for the policymakers. It is to inform their policies so that they can do a better job at creating programs and policies that improve, you know, healthcare.

So, what I do in my research — and this is a lot of thanks to NIMH and their, you know, sort of prioritization of advisory boards, for example, and dissemination and impact — we have policy — policymakers that sit on our advisory boards and are part of, you know, the research process from research generation to dissemination of results.

I sit in on meetings with policymakers all the time at briefings, discussing our results, and trying to have them understand sort of the evidence that we generate. And so, it is a very important part of my work. And I hope it’s — it becomes a more important part of most researchers’ work.

KIMBERLY BOLLER: Hi. Thanks so much. I’m Kim Boller from the American Psychological Association. I so appreciated hearing about the use of many different methods, including the hybrid method and also secondary data analysis of the Medicaid data, for example.

As you’re thinking about the workforce of the future and truly addressing population health issues, what are you seeing as the need for pathways and training for folks to do the kind of work that you’ve been doing? Thanks.

ASHLEY HAGAMAN: I think a lot of it is just inviting all the different disciplines into projects. And so, we have anthropologists and psychologists and economists that are all working on the same team together.

And so, I think a lot of it is when you bring those disciplines together, there’s so much, like, new shared knowledge and, like, systems and how people think and how people work. And a lot of the ways that we try and do that is by bringing in our community members, and they have an equal seat.

And I think in terms of, like, building the next generation, a lot of what we do is just create structures within our research team for pipelines and pathways for people to grow in their careers.

So, a lot of times in low-income settings where I work, there’s sort of this, like, perpetual research assistant. And we want to make sure that those bright shining stars get into leadership roles at some point. And so, we’ve started to create a lot of pathways for that in the teams that I work.

SERENA CHU: Yeah. Brenda, we’ll take you as the last question, and then we’ll go to break.

BRENDA CURTIS: From NIMH. And I have a question from a participant who’s online, and it’s for Dr. Rodman. What do you feel is lacking in the country’s education system to support the elimination of mental health stigma? And they go on and say, starting by partnering in communication with adolescents?

ALEXANDRA RODMAN: This is a great question. In some ways, I think we’ve come a long way with stigma in terms of there being a lot more open conversation surrounding mental health needs.

I think a new phenomenon that, at least in my work, we’re discussing with our — actually our focus groups with our adolescents, is the fuzzy definitions now of mental health disorders and the boundaries between —

Everything exists on a continuum, right? So, it’s like while we’re trying to operate within this taxonomy of, like, discreet boundaries, it’s not how the real-world works.

And so, I think trying to de-stigmatize mental health while still not over pathologizing has been a difficult balance for teenagers today, especially with, like, TikTok and these, like, influencers who are kind of co-opting the conversation.

And experts, I think, have difficulty kind of penetrating that conversation with more, I think, informed perspectives that may not — that don’t cause undue harm. So, I think it’s a really important area of conversation.

And something I want to kind of add to that, that has been circulating my mind as some of these other comments have come up, is something I think we should think about is the system as it is — you know, psychiatry operating within the medical model — the system itself is quite porous for a number of reasons.

And as a nation, historically, we very much value patient privacy. But what I’ve seen — this is not my research hat, this is just kind of like a person [laughs] — a former clinician and now walking through the world, is — what I’ve noticed is that, you know, at 18 years old, adolescents don’t suddenly become adults, right?

You know, there’s still — it’s still very much within a developmental phase. And yet our approach to care is very individualized. And I don’t mean from a precision perspective. Because I very much support the precision movement, and, you know, we’re hoping to do a little bit of that ourselves. But what I mean is that the adolescent-existing context, right?

And so, I think that mental health care would also do well to really think about that tension between treating the patient as a — as an individual and respecting privacy and ethical boundaries but starting to expand care to incorporate families and other support networks that would help kind of bridge some of these gaps that just we hope — we wish did not exist, but simply do exist.

So, we’re not picking up the pieces after, you know, an episode, but preventing it in the first place. Because we all know the costs that come along with having to then recover from an episode, for example. Yeah.

SERENA CHU: Thank you. We give a hand to our guests.

[applause]

Thank you for very wonderful presentations. I just want to remind everyone that we’ll break until 2:15 p.m. And just a reminder that there’s no food or beverage permitted inside the theater. So, please consume all those items in the lobby. And can the NIMH Planning Committee and Event Workgroup 3, please assemble on the stage, so we can take pictures? Thank you.

(Whereupon the Subcommittee members took a brief break starting 1:55 p.m. and reconvening at 2:15 p.m.) 

Transcript

MAURA LANDERS: Thank you, Dr. Bellamy, for your inspiring presentation. Can I just get another round of applause? Because she really took the theme and very inspiring. So, thank you. 

My name is Maura Landers. I am a program analyst in the NIMH Office of Science — oh gosh, Policy Planning and Communications. And I will be the moderator for our first session.

Just to note that for today’s sessions, your speakers will be introduced and their talks will continue in succession. So, I’ll go through everybody’s bios first, and then folks will come up. Following the last talk, all speakers will return to the stage for discussion and audience questions.

Now I have the pleasure of introducing the speakers for our first session. Dr. Michael Wells is an assistant professor in the Department of Human Genetics at UCLA. Dr. Wells earned his PhD in Neurobiology from Duke University, and he completed his postdoctoral training from Harvard University before launching an independent research program at UCLA. His research focuses on the genetic factors that govern the early development of the human brain and ways in which these processes lead to variation in human traits and disease.

Next we have Dr. Antonio Fernandez-Ruiz, an assistant professor in the Department of Neurobiology and Behavior at Cornell University. Dr. Fernandez-Ruiz completed his PhD at the University of Madrid, where he developed and applied machine learning methods to study the biophysical basis of brain dynamics. The mission of his lab at Cornell is to understand how neural neuro dynamics in distribution brain circuits support complex cognitive functions, and how small imbalances can lead to pathological states.

Next, we have Nicole Provenza. She’s an assistant professor in the Department of Neurosurgery at Baylor College of Medicine. She received her PhD in Biomedical Engineering from Brown University and completed her post-doctoral fellowship at Baylor College of Medicine. Dr Provenza’s research focuses on the neurophysiological underlying cognition and emotion and the effects of neuromodulation on neural activity and behavior.

And finally, we have Dr. Brielle Ferguson. She’s an assistant professor at the in the Department of Genetics and Neurology at Harvard Medical School, and an assistant professor of the Department of Neurology Research at Boston’s Children’s Hospital. Dr. Ferguson completed a PhD at Drexel University College of Medicine, followed by a postdoctoral fellowship at Stanford University. As a systems neuroscientist, her lab focuses on characterizing circuit mechanisms of attention and cognition, with the goal of identifying novel biomarkers that can be used to inform treatment approaches and a broad range of disorders.

And now, please welcome Dr. Michael Wells to the stage.

MICHAEL WELLS: Hi, everyone. I want to thank you all for joining me today and for giving me this opportunity to share with you my long-term vision of a genetics first approach to understanding human disease through the creation of something we are calling an atlas of human vulnerability. So, everyone in this room is differentially susceptible to a wide range of diseases in a manner that is at least in part, genetically encoded. Now this is especially true for highly heritable diseases like autism and schizophrenia, as well as other conditions that have strong genetic links, like Alzheimer’s, certain types of cancers and viral infection.

Now some of the earliest — some of the earliest work to quantify the contribution of genetics to diseases relied on twin studies and other ways of calculating heritability scores for these conditions. But something huge happened 20, 25 years ago, with the advent of human genome sequencing technologies that really pushed the field forward and allowed us to start identifying specific genomic loci that were associated with these diseases in different human traits. Typically, through these sorts of GWAS and large scale exome sequencing type studies.

Now the hope was that by simply identifying the genetic mutations and variants that were associated with diseases that we’d be able to very rapidly start developing treatments for these conditions. Hasn’t quite worked out that way, at least it hasn’t worked out at the pace that we were hoping. And really need to ask ourselves, why is that the case?

Well, as it turns out, perhaps unsurprisingly, the genetic landscape of human disease is quite complex. And the manner in which these genetic variants exert their effects and contributed to disease risk is they’re influenced by many different biological variables. This includes the fact that some of these risk variants exert their effects when they’re exposed to certain hormones. So, sex is an important biological variable. Age or developmental stage is important. Genetic risk for autism appears to manifest primarily prenatally, while genetic risk for Alzheimer’s obviously manifest much later in life. Environmental context is also incredibly important. We know that things like stress and pathogens and neurotoxicants can all influence the risk for various diseases.

Finally, ancestry is important. And I’m not talking about socioeconomic factors. You’re going to hear a lot about that today. I have already heard about that today a bit. I’m talking about biologically, what we’re talking about here is that different ancestral populations experience diseases quite differently. And in fact, one of the things that I’m most concerned about is the fact that there’s treatment resistance differences across ancestries.

So, for example, there’s many commonly prescribed drugs for asthma and certain types of cancers and diabetes that do not work as well in African Americans and Latino populations. And we need to really start to really start to think about how to combat that. Now, one of the main issues is that some of the existing technologies and approaches for answering some of these questions are limited in their ability to understand genetic risk and disease mechanisms in a manner that takes into account all these different biological variables.

So, we propose the creation of a sex developmental stage, context and ancestry specific catalog of the genetic and molecular risk factors contributing to human disease. And this is what we’re calling an atlas of human vulnerability. And through this, we hope to better understand genetic risk and thereby understand human disease, and then hopefully develop treatments based on this information.

So, obviously, this is not something that one lab can do. It’s going to require a lot of effort, a lot of money. I’m looking at you people who give out that money. But the question then becomes, well, what will my team, what will my lab, contribute to this massive endeavor? Well, to answer that question, we take a look back about 25 years ago to the beginning of the stem cell revolution.

So, by definition, stem cells can become any cell type in the human body. But it wasn’t until about 1998 that we’re able to harness that power for research purposes with the creation of the first human embryonic stem cell line. We’ve thus been able to generate what are called human induced peripheral stem cells, which really opened the door to being able to look at stem cells derived by — derived from patients.

Shortly thereafter, many different techniques to turn these stem cells in a dish to different types of brain cells. This has dramatically revolutionized our ability to understand human brain diseases using these in vitro models. So, it’s with this backdrop that as a postdoc in Kevin Eggan’s group and in collaboration with Steve McCarroll at Harvard Medical School, that we wanted to push it just a little bit further.

And the reason the real impetus for this was the fact that many of these in vitro studies looking at human patients were typically looking at a handful of them. So, three or four patients, three or four controls, and most of these types of experiments. And as I just mentioned, that means there are certain biological variables that will not be factored into those studies.

So, we developed a platform that enables population genetic studies in a dish. We’re calling this a cell village. The way this works is you take cell lines from many different human donors. They can represent different sexes, ancestries, and disease statuses. And we can get anywhere from 10 to 150 people represented in these villages.

What we do is we culture them all into the same dish. And by doing so, we are eliminating a lot of the technical variation that can reduce your ability to identify genetic signal using more conventional approaches when you culture these cell lines separately. The other real big advantage is that because they’re in a uniform environment, now we can isolate genetic contributions to how these individuals respond to different cell extrinsic factors like developmental signaling molecules, viruses, toxicants and even therapeutics.

So, our hope is that using this system, we’ll be able to better understand human disease, as well as identify biomarkers for — if you’re susceptible to viruses or toxicants, or even a biomarker for whether or not a drug is going to work in you. So, how exactly this work? I’ll spend just a minute or two talking about some of the features here.

Essentially, we can do high throughput phenotyping in this uniform environment. We can look at the cells in our village at the molecular level, using this tool that involves single cell RNA sequencing. And then re identifying the donors based on their natural barcode. So, the barcode is their genome, essentially. So, this gives us donor level gene expression profiles. So, we can do, say, differential gene expression analysis if you have patients and controls in the same village. And we can also build these gene co-expression networks that are quite valuable for understanding the molecular environment of a cell.

We can also do cellular phenotyping using the village system. There’s a tool we call census-seq, and it’s doing exactly what its name implies. It’s running a census of the village. Who’s there and what percentage of the village they represent? As you can see, you can do growth assays or viability assays by measuring over time how donor compositions change. Some might increase their presentation, others might decrease. And that gives us valuable phenotypic information.

We can also run facts based assays, which essentially means you can separate the cells in the village based on different markers. Say, a marker for cell type identity, or say, a marker for DNA damage. Whatever it is, you can then do census-seq on those different fractions and use that as a quantitative phenotypic score on a per donor basis. So again, we’re doing all of this on 100 people, you know, in the same dish.

So, one of the real selling points of the village system to me is the fact that we can then take all these different data types we generate from the same batch of cells and start integrating them, which means we can cut across different levels of biology. We can, for example, identify relationships between alleles and specific cellular phenotypes in our dish. We can identify genetic variants that influence the expression of nearby genes. And of course, we can find relationships between gene expression profiles and specific cellular phenotypes. So, we are getting a comprehensive understanding of disease mechanisms in a dish using the system as well as I mentioned, identifying specific variants that might confer that risk.

So, what is my lab doing? Let’s get into the present a little bit more. As mentioned, we focus on human development, human brain development, I should say. And there are four research pillars that we’re either currently addressing or plan on addressing in the very near future. These include genetic models of autism spectrum disorders. We’re also interested in identifying biomarkers for risk for environmental neurotoxic hints, as well as neurotropic viruses. And finally, we want to get into pharmacogenomics, which is the study of how your genome influences drug efficacy. So, influences how you respond to a therapeutic treatment.

I’m going to give you a couple of snapshots of some of the work that we have either published or are currently working on. This one was published in 2023 in cell stem cell. And this was our first demonstration of the village for this type of work. So, we were studying the Zika virus. And we’re trying to understand what are the genetic biomarkers for risk to Zika virus. And so, we’re looking at human neural progenitor cells that we created and put into a village.

And the first thing we noticed is that some donor lines were being demolished by this virus, and others were very resistant. And so, to understand that, we used the village system. We molecular profile these cells that are cellular phenotyping. And in doing so, we’re able to identify a single variant in the whole human genome. A single variant that could explain almost 60 percent of the variation in infectivity.

And in doing so, we have nominated that variant, which is in a very powerful antiviral gene. We’ve nominated that variant as a risk factor for Zika susceptibility. We’re following up on this work by looking at other neurotropic viruses like cytomegalovirus and measles. Using the same concept, we’re now trying to tackle neurotoxicants.

So, the first one we’re focusing on is lead. Lead is a very pervasive neurotoxicant. Unfortunately, it does appear to differentially affect minority populations and low income individuals. And so, it has detrimental effects on brain development. So, again, one of the first things we identified was huge variation in susceptibility. Some donor cell lines were quite resistant to the effects. Others were being demolished by this heavy metal.

So, we’re in the process of understanding both the molecular and genetic contributions to that risk, doing some of the types of experiments I just mentioned before. We then hope — I should mention, we hope to expand this to other neurotoxicants like arsenic as well as ethanol, and some novel emerging neurotoxicants like pesticides and forever chemicals. Okay. And I also mentioned that we are very interested in genetic risk factors for autism.

So, in this case, we built a village of neural progenitor cells that consist of neurotypical controls, as well as patients harboring a micro deletion of 16p11.2 chromosomal region, which is a major risk factor for autism. And at baseline, just culturing these cells and looking at looking at them in a dish, we didn’t see dramatic differences between patients and controls.

What really jumped out at us was when we started stimulating these cells with different important signal transduction molecules that play important roles in brain development. And that is what started to show some of these really interesting potential disease mechanisms. Specifically, we noticed that these patient lines are hyper responsive to sonic hedgehog activation, which can have traumatic effects on neurogenesis and dorsal ventral patterning of the brain.

So, we’re following up on this in two ways, trying to understand what are the consequences of this on brain development. And also, trying to understand why exactly this is happening in these cell lines. We’re excited about this idea as a whole because it potentially opens up this avenue where we can start looking at genetic models of autism and start systematically characterizing their responses to these important signaling cues, which we think will reveal some of these sort of hidden disease mechanisms.

Okay. So, that’s what I’ve been doing. What do I hope we’re talking about at the 100th year anniversary of the NIMH in which we look back and say, “Look how big and important villages were.” I hope we can say that villages played a really important role in accelerating the personalized medicine revolution. So, what do I mean by this? Well, we typically perform drug screens in a handful of cell lines. And as I mentioned, that means many biological variables are not playing a role — or not being considered in that type of screening assay.

So, what if we could actually perform the drug screens in a village? So, that’s — pharma companies or researchers are actually moving forward and prioritizing the compounds that were safe and effective in a large portion of the human population. This could potentially start to alleviate some of those disparities I mentioned with existing drugs that do not work well in some patient populations.

We could also then identify the biomarkers that are linked to response or non-response to some of these treatments and that can help in the design of clinical trials. Imagine being able to determine ahead of time whether or not someone would be a responder or non-responder in designing your trial around that information and using that genetic biomarker as a way of selecting individuals.

Finally, along that same idea, if we had biomarkers for efficacy of some of these drugs, that could help doctors prescribe the correct drug or the most effective drug to patients, rather than going through this trial and error period that is actually quite common in psychiatry. Okay. They asked me to think big. And so, I’m going to think really big here. So, bear with me for a moment.

I believe that villages can also help us understand where we came from and where we’re going. So, I think villages can be used for evolutionary studies. We can model past scenarios that humans have endured, that have shaped the human genome. So, these sort of selective sweeps, whether it be famine or viruses or migration or climate change. And we can model this in a dish and ask what were the mechanisms that drove us that natural selection and shaped our genome?

Here’s where it starts getting a little wild. A lot of people want to leave Earth and go to different planets. Sometimes I feel like I’m one of those people, and there’s some issues with that. We know that astronauts are exposed to higher levels of radiation while they are off our planet and traveling. This is a major concern for our ability to do this sort of space travel. And so, by modeling that radiation and identifying biomarkers of resistance, we can actually leverage that information to potentially create preventatives that minimize the effects of this radiation on people who are traveling up to other planets.

And also, if we actually get there, we actually get to one of these different planets, that’s going to be a novel environment for people. Also, if we stay here on Earth, there’s likely to be novel environments, given the rapidly changing climate that we’re experiencing. I believe villages could help protect us from those changes by helping us identify and model those future scenarios, so that we can find biomarkers of resistance. And then leverage that information, leverage that genetic information, to develop preventatives for something that happened — if something like that were to happen.

So, with that, I want to thank you for your time and indulge in me with some of these wild ideas. And I’ll leave a slide up while the next presenter comes up.

ANTONIO FERNANDEZ-RUIZ: Well, hello everyone. It’s my privilege to be here speaking in this great symposium. Thank you to the organizer for having me. So, today I’m going to be talking about some of the recent work from my group and how I believe it can inform some future avenues for the research of the medical basis of mental health disorders, as well as for the development of new therapeutic approaches.

So, I want to start by highlighting a very well-known fact that many neuropsychiatric disorders, ranging from Alzheimer’s to depression or schizophrenia, they have a variety of causes. They can be genetic mutations in specific genes. They can be environmental factors related to lifestyle or diet, or they can be developmental alterations.

And on the same way, they are characterized by a broad diversity of symptoms, from cognitive decline to affective disorders to psychotic breaks. And you know, traditional approach, let me see — traditional approaches have been typically focused on taking one of these causes and trying to dissect them to understand them in detail, or focusing on the mechanisms of some specific symptoms.

And I want to propose today a somewhat complimentary approach, by trying to identify common principles, point of convergence across different causes, across symptoms. And we already have a spoiler here because what I’m going to propose is going to be a point of convergence across many of these different causes for multiple diseases are disruptions in neural circuit dynamics in a specific circuits in the brain. Such disruption in neural dynamics lead to impairment of information processing in the circuits.

And I believe that these impairments of information processing and one of the major underlying causes of a cognitive and other types of symptoms that are common across multiple disorders. So, I hope by the end of the talk, I can convince you that there is some value of taking this approach by identifying this point of convergence and try to both understand them and target them for therapeutical means.

Yeah. So, traditional approaches to treatment of mental disorders, for example, for macrological approaches, have been very successful in many cases, but also have some important limitations. Among them, for example, that the effects can be delayed respect to the appearance of the symptoms, and there can be difficultly adjusting in a dynamical manner.

So, the complementary approach I am proposing is based on providing on demand manipulation of neural dynamics based on the detection in real time of abnormal patterns of activity. And these this approach has some clear advantages, such as providing a high spatial and temporal specificity, and can be based on the detection of early biomarkers.

To explain the process, more clearly, I divided in four stages. And I’m going to be briefly explaining them first and then showing some work that we have been doing in each of them. So, first we need to identify dysfunctional biomarkers. And this can be done by performing, for example, brain wide recordings of neural circuits in both human patients and animal models. And I’m going to highlight the value of this comparative approach of comparing animal models and human.

And then we would like to not only detect, not only identify these biomarkers, but to predict them. So, to be able to intervene before alterations even appear. And we have made some progress on this by leveraging machine learning approaches to the analysis of neural data sets. And then the key step is to try to correct these alterations by providing closed loop intervention.

And finally, the last step is to evaluate how this closed loop intervention actually improve cognitive performance. And again, we can start with animal models, with the goal of translating this knowledge to humans.

So, in the first part of my talk, I’m going to show how I believe brain oscillations in particular can be an excellent biomarker of cognitive decline across multiple diseases. And to make my case, I’m going to focus in only one specific type of neural pattern. These are the so called hippocampal ripple oscillations.

So, the hippocampus is this structure in the in the medial temporal lobe that has been shown to be fundamental for learning and memory processes. And its activity is characterized by the presence of those oscillations that I have an example on my screen. These are very high frequency patterns, more than 100 hertz. And they entrain the activity of hippocampal neurons and tend to appear mostly during a slow wave sleep and processing behavior.

So, a remarkable fact of hippocampal ripples that actually is common to other oscillations is that they are present across many animals, virtually across all mammals, with very similar characteristics and underlying cellular mechanisms. So, I think this highlight the point that using these type of patterns by studying them in animal models have indeed a translational potential. And there is a lot of work showing the importance of these hippocampal oscillations in learning a memory. I’m just going to highlight a couple of studies here from humans.

In this case, epileptic patients, when implanted with intracranial electrodes in the in the hippocampus to recall ripples, and they were showing a series of pictures. And after some delay, they were asked to simply recall them. So, when patients were recalling the pictures that they learned before, ripples appear in the hippocampus. And so, this result led to [unintelligible] ideas, memory recall correlate with the presence of this type of oscillations.

But, you know, complex cognitive functions such as memory recall do not depend on only one brain area, but on the activity of many circuits and many areas across the brain. So, this other study actually from the NIH recall at the same time the hippocampus and many cortical areas in human patients. And they show that during the performance of memory task, the hippocampus will produce these ripple oscillations. And they will propagate to the whole cortex and entrain activity in these regions. And this communication was essential for memory performance.

And the cellular basis of that explain why ripples have this important role in memory have been worked out by us and many other groups before in rodents mostly. Here, I bring a very simplified example. Let’s imagine that a rat, for example, discover a tasty reward of a corridor. So, when the rat is running from left to right in this corridor, different hippocampus cells will be active in in succession.

So, the sequence of hippocampal cells encodes this trajectory that led to the cheese. So, when the animal goes to goes to sleep, ripples appear in the hippocampus. And the remarkable finding was that the same cells that encode this experience of running along a trajectory and discovering cheese are active during sleep in these hippocampal ripples. And even they preserve the same order of the experience. So, we believe that this sequential activation of hippocampal neurons during a sleep leads to synaptic plasticity and the formation of memories.

And in support of these hypotheses, several studies like the one I am showing here did a disruption of ripples. So, in this case, the rat was learning a special task on a maze, then went to a sleep. And then we disrupted, specifically hippocampal ripples. And what we obtained was that memory was severely impaired. So, establishing a causal relationship between this pattern of activity and memory.

And a wide variety of studies have come out in recent years showing how hippocampal ripples are impaired in different genetic models of disease in rodents from Alzheimer to epilepsy to schizophrenia, suggesting that they can be an important biomarker to predict cognitive decline in these diseases.

And I’m going to highlight just one example from our own work. In this case, we were studying a mouse that has a mutation, a chromosomic deletion that replicates a very common one found in humans that indicates predisposition for schizophrenia. It’s a deletion in the 20q 11 chromosome. So, these mice, this genetic mouse model of a schizophrenia predisposition, they have memory deficits, even in very simple tasks, such as recognizing that an object has been moved.

So, they perform much worse than wild type mice. And what we found was that they do not only have these behavioral impairments, but specifically, ripple oscillations in the hippocampus were impaired. And as you can see in the blood trace, ripples were much smaller and shorter. And even more, the degree of impairment in this hippocampal oscillations correlate with the degree of impairment in memory task, suggesting that there may be a causal relationship there.

So, what I would like you to remember from this part of the talk is that brain oscillations are universally conserved biomarkers of cognitive functions. And in particular, a highlighted example of hippocampal ripples as a potential substrate for memory, and they can also be a useful biomarker. So, what I envision as a potential avenue for the future is start to try to identify similar alterations in brain oscillations that can be recalled by noninvasive or invasive means in humans as a biomarkers of cognitive decline in different diseases.

Okay. And now I’m going to show in this, in the second part, how I believe we can leverage this type of basic knowledge, to develop new therapeutic interventions. And the basic approach I am going to be defending is this on demand intervention that is based on performing in the first place recordings of brain activity can be done by any means now invasively and try to detect neural signatures or biomarkers of cognitive functions, such as, for example, will be the case of hippocampal ripples.

And then upon the detection of this neural signature, the liver intervention can be, for example, with the transcranial magnetic or electrical stimulation in a noninvasive manner. And evaluate how this intervention affects the symptoms and reiterate the cycle.

So, despite some clear advantages of this approach as a high temporal specificity, it has not been widely applied. And perhaps, the most well-known causes of success are Parkinson’s and epilepsy, but not many, many other diseases. And I believe the reason for this is that for many other diseases, we lack clear functional biomarkers. And we also lack an understanding of the specific circuit and cellular basis of this abnormal activity. And perhaps more importantly, we lack tools for selectively intervening, especially in patients.

So, while there is still a lot of work to do on this sense, we have made some progress, starting with the rodents. I’m going to briefly highlight them here. So, a few years ago, we identified that when rodents were successfully performing memory tasks, this hippocampal ripples that I mentioned before became longer. And there was a very clear correlation between the length of these, these patterns of activity, and the successful performance in memory tasks.

So, we have this idea that okay, whether — will it work if we try to artificially boost these oscillations and make them stronger, make them longer? Will that have any beneficial effect on animal performance? And to do that, we took advantage of a technique called optogenetics, which allow us to express artificial ion channels in selective neurons. And these ion channels can be — in this case, in the hippocampus. These ion channels can be activated by light that we deliver with optic fibers implanted in the in the rat brain.

So, by doing that, we were able to detect in real time these oscillations and boost them, make them stronger, longer. And we apply that to animals, to rats, doing memory tasks. And what we found was that, yes, indeed, it improved memory performance, which was a big, a big surprise for us.

But, you know, this is only one type of animals. So, can this be applied to disease models? So, we don’t know. But some promising evidence is that in all animals, all mice, and same model mice, the ripple, the hippocampal ripples are also shorter. So, we speculate that by boosting them, maybe we can also restore the cognitive deficits.

So, in the last minute that I have, I just want to highlight some future directions that I believe may be important and hopefully come to fruition in the next years. One is to try to move away from simply detecting abnormal brain dynamics, as, for example, commonly known in epilepsy with seizures, to try to predict them, to anticipate before they happen. And we have done some progress applying machine learning methods in the sense.

They also develop noninvasive techniques. Because optogenetics is very useful in rodents but can be hardly translate to humans. So, there are other means, and we have done some things using transcranial electrical stimulation and trying to focus it to a specific brain circuits. And using this circuit information derived from animal studies to inform our interventions. With the hope to develop a suite of electroceutical treatments that can be applied to human disease.

So, with that, I just want to thank you my lab members and funders, and to all of you for listening.

NICOLE PROVENZA: Hi everyone. It’s truly an honor to be here. My name is Nicole Provenza, and I’m an engineer by training. I run a lab in the neurosurgery department at the Baylor College of Medicine in Houston, Texas. And I’m really excited to talk to you all today about the future of neuromodulation for mental illness. And my title side image shows an artist’s rendition of the particular type of neuromodulation that I focus on, deep brain stimulation.

DBS allows patients to break through and become unshackled from the hold of mental disorders. So, similar to how pacemakers regulate electrical activity in the heart, DBS regulates electrical activity in the brain. And precise tuning of the stimulation parameters allows the electrical pulses to restore a dysfunctional circuit back to a healthy state.

DBS is commonly used to treat movement disorders like Parkinson’s disease. And it’s being used more and more for treatment resistant psychiatric disorders like OCD and depression. DBS for OCD is approved by the FDA under a humanitarian device exemption. And it’s the only psychiatric disorder for which DBS has FDA approval.

And in OCD, two out of every three patients that undergo DBS surgery actually receive significant clinical benefit. And this is really amazing, because these are patients that have tried everything else out there, everything under the sun, and nothing has helped them before. And these are the patients that I work with the most.

So, I’m going to show you a quick video of what initial stimulation looks like in a patient with OCD. And we and others optimize lead placement in the operating room based on acute responses to stimulation. And one of the things that we often see is a description of increased energy and motivation. And this really looks different for everyone. So, I’ll show you this video.

[start of video]

MALE SPEAKER: Okay. Yeah, I mean, like an 11 [unintelligible] something.

MALE SPEAKER: It’s good, though, right?

MALE SPEAKER: Yes, very good.

MALE SPEAKER: What do you feel like doing?

MALE SPEAKER: Jumping out of an airplane.

MALE SPEAKER: With a parachute?

MALE SPEAKER: With a parachute, yes.

[end of video]

NICOLE PROVENZA: So, just so you know, this patient was homebound for years before having this surgery. It was like a miracle that this patient actually showed up at the hospital that day for surgery. So, as you can imagine, these effects are often really profound and exciting to see. And we actually think these acute effects are promising indicators of ventral response, but we don’t see improvement in OCD symptoms per se until weeks or months after continuous stimulation.

So, this time, lag between stimulation and actual symptom changes makes tuning stimulation really difficult and high burden for clinicians and patients. So, before I talk about the future, I need to talk about the present. Currently, DBS for OCD is open loop, requiring several visits to the clinic after DBS is turned on for the first time to optimize simulation parameters. And so, patient comes into the clinic. DBS is turned on or adjusted.

Patient says, “I think I might feel better, or I feel like jumping out of an airplane.” And then they go home. They might feel great for a while. Over time, their symptoms, you know, reemerge, or maybe they’re always there. They go back to the clinic weeks to months later, and they don’t feel better anymore. And so, what we’re proposing is that automatic detection of mental states related to symptoms and side effects would enable data driven intervention.

And so, what would this look like? Modern DBS devices can record neural activity from the brain during ongoing stimulation. So, we can continuously collect both neural and behavioral data at home, process the data and maybe send an alert to the clinician when it’s time to check in with the patient. Maybe they need to give the patient a call. Maybe a medication or therapy augmentation is needed, or maybe we can deliver an automatic stimulation adjustment.

And I think this strategy has the potential to decrease patient and clinician burden and improve outcomes by better managing symptom fluctuations. So, what do we need to do to get here? I’m going to cover three broad themes that I think themes — are themes of this session.

First, we need to better understand the brain behavior relationships underlying psychiatric disorders. So, a better understanding of these disorders would hopefully lead to biomarker identification. Maybe we could identify biomarkers that tell us when neuromodulation is working versus when it’s not. Or when someone is relapsing.

And this brings me to my second bullet. This improved understanding would allow us to develop smarter, personalized therapies that improve outcomes. And we could do this by dynamically modulating the therapy to better control symptoms and side effects, or by better matching patients to therapies.

And lastly, and perhaps most importantly, we need a feature where engineers and clinicians partner together to develop neuromodulation devices that patients actually want to have. And first, I’ll start by talking about biomarker discovery, where we are, and where we’re going.

So, beyond obsessive compulsive disorder, DBS has been tried in a smaller number of patients with varying degrees of success in a lot of other disorders, including depression, Tourette Syndrome, addiction, and substance use disorders and eating disorders. And definitions of these various diagnoses rely on symptom phenomenology.

For example, we diagnose someone as having OCD based on the presence of obsessions and compulsions. And while these are known as the defining features of OCD, more broadly, these symptoms can be thought of a manifestation of cognitive rigidity, or put more simply, stuck ways of thinking, which can also be a prominent feature of other disorders like depression and anorexia, for example.

So, over the last 10 to 15 years, there’s been a push toward conceptualizing disorders within a trans diagnostic framework. So, it’s possible for several individuals diagnosed with different disorders to overlap on the same dimension. But it’s also possible for several individuals with the same diagnosis to separate across that same dimension.

And so, in this example, depression can manifest as cognitive rigidity, but it can also manifest as a melancholic subtype or as flat affect. And we think knowing where individual patients lie on each of these axes is an important step toward identifying neural biomarkers, because we think there’s a shared underlying neural mechanism related to dysfunction in each of these domains, regardless of diagnosis.

So, the way that these constructs are classically studied is by pairing computerized behavioral tasks with concurrent neural recordings. And we’ve learned a lot using these task based methods, but we don’t yet know how performance on a behavioral task while someone is sitting in a computer looking at a screen translates to real world behavior.

So, over the past 10 years, the field has really been moving toward more and more naturalistic paradigms. So, instead of a task, we can have someone watch a movie, play a game in virtual reality, or we can even study behavior in the real world using data collected from wearable sensors or their phones.

And so, this is exactly what doing to identify biomarkers in patients implanted with recording capable DBS devices. We can record high quality neural data in the clinic and at home while patients are going about their everyday lives. And there have been several studies using these more naturalistic strategies in OCD over the past five years.

And really briefly, in 2021, our team, in an N=3, identified Delta band as a biomarker related to OCD distress. In 2019, before us, in an N=1, Miller et al identified gamma band as being related to provocations of OCD symptoms. More recently, the Penn group in an N=1 identified that it was actually delta theta alpha and beta activity that’s related to increases in OCD symptoms.

And our colleagues at MGH, Vusani et all, and an N=2, found that actually it’s alpha that correlates with OCD symptoms. And so, this is by no means an exhaustive list. But using these snapshot style, few minutes at a time recordings and small end studies, there really seems to be a lot of heterogeneity and little to no consensus about what the biomarker is for OCD. And there’s clearly something more complex going on than elevated power in a single frequency band. Maybe we need to zoom out and look at longer time scales to figure out what’s really going on.

And so, for this reason, our work has focused on looking at longer time scale fluctuations. So, clinical response in OCD is classically assessed using the Yale-Brown Obsessive-Compulsive scale or the Y-BOCS. And it monitors symptom activity over the past two week period. And our goal was to link clinical response to neural activity and identify neurophysiological markers of clinical status by continuously monitoring neural activity in the real world, in the background of everyday life activities.

And the real life part is really important because 99.9 percent of real life actually happens outside of the clinic. So, we set to — we set out to identify what the biomarker is for these slowly evolving states relevant to DBS for OCD. And we conceptualized OCD as a disorder of pathologically avoidant behavior, where compulsions are an irrational manifestation of that avoidance, and appropriate levels of stimulation induce positive mood and energy effects, as you saw. And it eventually allows patients to become more approachful and less fearful of their triggers.

Overstimulation, on the other hand, can often induce significantly disinhibited behaviors. And our work was recently published in Nature Medicine. And we identified a biomarker of clinical status based on these everyday, 24/7, real-life recordings.

So, we used the implanted DBS device to record neural power every 10 minutes, 24/7. And so, here, I’m showing you days since CBS activation on the X axis and time of day on the Y axis. I have two example patients, a non-responder on top and a responder on the bottom.

And before DBS, at the vertical pink line, you can see that in both patients, there’s clearly a peak in brighter blue happening sometime in the morning and a trough in darker blue happening later in the day. And we call this a neural circadian rhythm. And it’s really consistent before DBS.

After DBS, in the non-responder, this pattern is extremely consistent. And it’s actually stable throughout the entire yearslong monitoring period. In the responder, however, something remarkably different happened. This pattern abruptly changes and evolves into a pattern that looks completely different than the pre-DBS state. It’s really high entropy and unpredictable.

And the feature that best captured this slowly evolving change is a measure of neural predictability estimated from our ability to predict future data points from past data points using a linear, autoregressive model.

So, you can see that in the non-responder, there’s no significant difference in the predictability after DBS, but the predictability of the neural data is significantly reduced after DBS for the responder. And this finding held up in 12 patients. And it’s completely changed the way that I think about neural biomarkers for psychiatric disorders.

This work tells us that neural biomarkers of slowly evolving clinical states relevant to psychiatric disorders might not be episodic variations from baseline, but rather features of the variation in baseline itself. This theme seems to really be picking up steam. There is work published last year by a group, Georgia Tech, Emory, and Mount Sinai, where they were looking for neural signatures of depression based on daily, real-world recordings on board DBS devices.

And they found a biomarker that evolves over the same time course as typical symptom changes, which in depression is weeks. And this work could be useful for distinguishing treatment — for distinguishing transient distress, unrelated to depression, from depression relapse. In the case of transient distress, further intervention might not be needed. But in the case of relapse, we could use this biomarker to potentially identify danger zones to intervene before the patient descends into another depressive episode.

So, the tools exist to do these recordings, and more are coming. There’s two available — two devices that can chronically track neural data available in the U.S. today. But more of these are on the rise and being developed all over the world. And we can pair these devices with the use of synchronized peripherals and wearables that can track ambulatory behavior. And these approaches are — relating chronic, ambulatory, neural activity with deep behavioral phenotyping, I think are only going to become more prevalent and widely used.

I want to highlight one example of how we can use passive behavioral monitoring to gage clinical status. So, this is from Justin Baker’s lab at Harvard. He’s using wrist accelerometry to measure activity levels in patients with depression. So, from top to bottom, he plots clinical rating, self-report, activity levels, and sleep. Red means more activity, and blue remains less activity.

So, looking at this data, it’s clear when the patient’s sleeping, in blue, and when they wake up, in red and orange. And what’s really cool though, is that when the patient ratings start to slip into a depression state, there’s a clear change in activity pattern. It’s really obvious.

The blue representing the low activity periods when the patient’s sleeping start getting longer, indicating later wake up times. And the red starts to shift to orange and green, indicating less activity during the day. After the depressive episode, the activity returns to baseline values. And this is just one example showing how we can use Objective behavioral readouts to inform clinical status.

The last point I want to touch on is that in order to maximize the impact that neuromodulation can have on people with mental illness, we need to increase the acceptability of the therapy. Right now, there’s a tradeoff between effectiveness and acceptability, which I have plotted here on these two axes.

DBS can be really effective in treatment-resistant populations, but it’s really scary for a lot of people. It involves bur holes drilled into the skull and leaves implanted into deep brain structures permanently. And even for Parkinson’s disease, a movement disorder that is much less stigmatized than mental disorders, only 10 percent of candidates choose to undergo DBS for Parkinson’s.

So, in general, people don’t want this therapy. Noninvasive therapies such as transcranial magnetic stimulation, which involves a coil placed outside of the head, is highly acceptable because it’s noninvasive, but the stimulation is less targeted than DBS. Effectiveness is really great in the short term, but durability remains a limitation.

So, our target is to optimize each of these dimensions. Maybe this involves a minimally invasive strategy. There are many companies that have sprouted up over the last couple of years that are trying to do exactly this. And I think this is the sweet spot where we’re really going to be able to use neuromodulation to improve the lives of people suffering with mental illness.

And with that, I want to acknowledge my growing lab at Baylor and our funding through the NIH BRAIN Initiative. Thank you so much for your attention.

BRIELLE FERGUSON: All right. Hello, everyone. I’m Brielle Ferguson, and I’m super excited to talk to you about some work that is going to be structured a little bit differently than some of the other talks that you’ve heard today.

So, I’m going to be talking about the history and impact of some of the recent grassroots movements that are largely trainee led, really aimed at diversifying the sciences. And I’ll also talk about how my participation in that work has really served as such an important catalyst for my own career trajectory. And I credit it so much with me being where I am today.

But for you to really understand that, I have to take you back a little bit to kind of who I am and where I came from and how I came to science and really who I thought a scientist could be and more importantly, couldn’t be.

So, I grew up in a small town in central Virginia. And if you would have asked me to picture a scientist, these were the images that came to mind. I only saw scientists that look like this, whether it was in my classroom, whether it was in textbooks, whether it was in the media. And this is not a new idea. We know that you can’t be what you can’t see, but I think it bears repeating. Because it really does shape what you think is possible.

And so, I graduated from high school without a strong sense of direction. I did relatively well in school. And I thought people who do well in school, they go on into medicine [laughs]. I didn’t know what the other options were. And with the incredibly supportive parents that I had, they didn’t have the cultural access to provide exposure to other types of options for me.

So, I went to the University of Virginia thinking I was going to pursue medicine. And because of limited time, I won’t take you on all of the things that happened in between. But ultimately, I was really excited by psychology and the puzzle of the human brain. But where I really found my home was neuroscience. Because I realized that it gave me the ability to not just describe but also really get under the hood and understand, down to small groups of cells, how they contribute to particular behaviors.

But — so, I decided to apply to grad school. But as you can see with this tortuous path that was littered with many, kind of, unsuccessful completion of courses, I was a tough sell to graduate schools. And so, I was rejected by every graduate program that I applied to, with the exception of one. And to this day, I am so incredibly grateful to Drexel University College of Medicine for really taking a chance on me. Because I credit them with kind of giving me the foundation of being where I am today.

So, started in graduate school at Drexel University College of Medicine. This is me at my first poster presentation. Completed my Ph.D. in 2017 and then went on to do a postdoctoral fellowship at Stanford. And along the way, it was not lost on me that as I looked around, and particularly as I looked up, I saw no one who looked like me. And it’s hard to kind of put into words the impact that that has on you, again, when you’re trying to imagine yourself kind of moving on to the next career stage.

And so, I went on to Stanford, really feeling the weight of that lack of representation, but I did ultimately go on to open my own lab at Boston Children’s and Harvard Medical School. And there were really two key experiences that happened along the way that I really credit with feeling like I could move on to the next step. And I’ll talk about each of those.

The first was at Stanford. There — we founded the — or not we — the first Black Postdoc Association was founded, and I was very lucky to be able to have access to that community and later be able to go on to lead that community. And the peer support that I found through that, making me feel like I wasn’t alone, validating My experience, was really instrumental in me feeling like I could survive through the postdoc stage.

So, have to thank the Stanford Black Postdoc Association and all of the Black Postdoc Associations that have been born from this idea around the country, that are helping other people feel like they’re not alone in this path as well.

The second was the pandemic. And this is not even to mention the lives lost and the physical and emotional consequences of that, but there was this separate layer that I experienced as a Black person, and particularly a Black woman, going — moving through the pandemic.

We all remember the story of Amy Cooper who called the police on Christian Cooper, who was bird watching in Central Park. And this was just one in a series of really horrific examples of racial violence towards Black people. And the difficult thing about this or the unique thing about this is this was not new. This has been going on since the founding of America.

But what was unique about this moment is that we weren’t able to turn away in the same way. We’re forced to have a real conversation around it. And from something really tragic, I think there were — something beautiful was born. So, Black Birders Week was [laughs] a week that evolved with a goal to highlight the stories of Black people to exist outdoors and affirm their right to be there without fear.

And they use the method of themed days with instructions, hashtags, and live events. And so, if you were to go on Twitter during Black Birders Week, you would see these beautiful posts of Black people out in nature. And I remember them just flooding my time on it and being so inspired by that and thinking to myself, is this something that we can do in neuroscience?

Black Birders Week kind of formalized lots of — or kind of catalyzed forming a larger group that brought together all of these Black and X groups that existed but were not in conversation with one another. And it built upon the efforts that so many people have been doing in the past that really put us under one umbrella.

And so, as I said, I was thinking to myself, is this something that we could do in the neurosciences? And I was lucky enough to see a tweet from our Co-Founder and Founding President, Angeline Dukes, asking, “When are we doing a Black in Neuro Week,” where we’re we going to do something like Black Birders Week but for us.

And so, I responded to this tweet. This was on July 3rd of 2020. We met two days later. We had our first meeting and secured all of kind of the infrastructure to start planning the week. We started making official announcements in all of our individual social media pages. We were able to secure some early sponsorship that kind of started the ball rolling for future sponsors. And then just a few weeks later, we had the first Black in Neuro Week.

Now, we had the goal of highlighting Black excellence in neuroscience-related fields. We wanted to help Black scholars build community. We wanted to help them provide resources specific to Black scholars and finally, increase visibility of Black scholars to those considering coming into the field or those currently in the field. And we borrowed directly from the methods of Black Birders Week in the two weeks that had come after it, before ours, and did this across social media platforms.

And so, this is just the — our social media posts from each day. And I won’t go through all of the details. But just to give you an overview, over the course of the week, we had several live events. We had seminars. We had panels. We had podcasts. And I think what was really exciting about it is we were able to really engage the community and get everyone excited about the work.

So, it wasn’t just Black scholars, it was allies. And everyone was sharing and supporting and amplifying. And at the end of that, we had built a database of over 500 Black in Neuro scholars that was searchable. And you could look for mentors. You could look for speakers. You could look for faculty candidates. And that’s only continued to grow.

So, for my kind of personal experience with that, as I said, I always struggled with finding Black peer support and particularly, finding Black mentorship. And I wholly credit the community that I found through Black in Neuro in being able to identify Black people who had gone before me who were not just existing in faculty roles, but really thriving and excelling and being able to learn from them and have them validate my experience and feeling like I could take the chance in going towards the next step.

But what’s happened since? So, we’ve kind of solidified our core goals, which is building community, providing professional development resources, and increasing visibility for Black scholars in neuro. And we target all of our programming and in my role as programming director around making sure we’re meeting all of these core goals.

So, just some examples, we had many, many — we’ve had many, many virtual socials that are all kind of centered around themes and sometimes in partnership with different conferences. And this is aimed at building community amongst Black scholars. Because so many of us don’t know other people that look like us. We’ve had professional development resources that are particularly tailored towards our community.

But an important thing to highlight is, for all of these, they’re open to everyone. And so, it’s a resource for us and by us, but it’s open for everyone to benefit from.

Finally, to increase visibility, we use our seminar series where we highlight people at various career stages and give them the opportunity to share their science and their journeys, again, to kind of validate the experience that so many of us have had. We can realize that we’re not alone and that we exist and that we’re thriving in these spaces.

So, what’s been the impact on the community? Just an overview of some of the programming and the numbers behind it. Since we started, we’ve had over 110 free events. And so, I highlighted that these events are open to everyone, but they’re also free. So, there are no restrictions to entry for anyone. And importantly, if you’re not able to access these events live, they’re all archived on our YouTube channel. So, you can go and find them as a catalog of resources for everyone at various stages.

We’ve had over 40 expert speakers speak across these events. We’ve had over 22,000 registrants at our events since 2020. And in just the last year, we had 1600 registrants. Throughout this process, though, we focused on steady, sustainable growth. And I think that’s really been the key in not us just starting the work but being able to sustain the work and be able to grow the community.

So, since the beginning, we went from just a few hundred members or 500 members that are — to over 1,000 members as of last year and then steadily growing. This community is made up of people across stages, but it’s largely trainees who need this mentorship and need this peer support and need these resources. So, we’re really proud of the community that we’ve grown. But again, we want the database of the community to be a resource for everyone.

In terms of what’s next, we’re excited about so many things. But some initiatives I want to highlight are our mentorship programs. So, there’s been informal mentoring that’s been happening throughout our community since the inception. But now, we’re kind of formalizing that and building in specific programming, targeting needs of our members.

We were also recognizing that our needs are evolving as time has gone on. So, we started during the pandemic. It made sense to do everything 100 percent virtual. But now, there’s a need to really grow those local communities, and we’re doing that through local chapters. And so, we had a pilot chapter in New York City that started at Columbia. And we’re using this as a model to begin to create these chapters or in — at institutions and cities around the U.S. and around the world.

So, in closing, what are some lessons learned from participating in the work? As someone who has led in DEI work at every stage, I think what can happen, and I think particularly in academia, is we can think that all of the solutions have to be perfectly executed. And we can let that slow us down from doing the things that we can do at the time. We think every solution has to encompass everything, and it has to be perfectly executed. And I think that can really hinder progress.

So, don’t let perfect be the enemy of the good. And When access is so severely limited, and Black and other underrepresented scholars are so kind of just starved for interaction with other people that look like them, the smallest efforts can go the longest way or the farthest.

So, here are some words from our community. “There are others just like me. My experience of interacting with zero Black neuroscience faculty at my local institutions is not unique.” And being able to see the really swell of support and excitement around other Black faculty around the world is changing how people view their place in neuroscience.

And then finally, final take-home, which is inspired by Dr. Bellamy’s talk, is listen to the authors. Listen to the people with the lived experience. I’ve been — in each role where I’ve worked in kind of leading DEI efforts, I’ve been so excited to be in the room with people who I think can actually allow me to make a change. And so many initiatives and so many ideas just kind of fizzle out at the workshopping stage.

So, if you have the opportunity, listen to the people with the lived experience, give them the space to do the work, and provide them with the resources, if you have that capability. Because I think you’ll continue to be amazed by what we can do. So, with that, I want to thank you all for your attention.

I want to tell you where you can find Black in Neuro work across all social media platforms but do most of our engagement on Twitter. I refuse to say X. You can also find us on at BlackInNeuro.com. And here’s some important links if you’re interested in supporting or finding that member directory, where you can look up all of our over 1,000 members. And at the bottom is where you can reach me. Thank you.

MAURA LANDERS: Thank you, Drs. Ferguson, Provenza, Fernandez-Ruiz, and Wells for your informative and thought-provoking talks. Now, I’d like to invite all — you all back up to the stage for discussion and questions from our live and virtual audience.

I do want to point out two things. One, if you’re joining us virtually, there is a Q&A function on the — not sure what platform we’re on, but there is a Q&A function. So, you can type your questions in there, and we will have someone read your question out loud here. If you’re asking a question in person, please make sure to use the mic so that those who are watching online can also hear your question.

I will join — it looks like we already have a question from Dr. Gordon. Please go ahead.

JOSHUA GORDON: Hi. Well, thank you. First, I want to thank all of you, not just for your wonderful talks, but also for the work that you’ve done that and that I’ve enjoyed learning about, not only today, but in the past. And that inspires me and many others. So, thank you very, very much. And I think we should give them all a round of applause.

[applause]

And one more note of thanks before we move — I move on to the question, I want to thank you, Brielle, in particular, for Black In Neuro. It is a resource, and I encourage everyone to do this. For me, when I’m trying to remember my colleagues, and I can — I can go on Black In Neuro. And there’s another list of women in neuroscience called anneslist, that I use very, very frequently as I’m trying to make sure that I’m inclusive when I’m thinking about who to invite to events or to write things, et cetera.

So, it’s a — it’s really wonderful resource for those outside the community as well, to make sure that we stay connected with those members of our community who belong to groups like that. It’s great. It’s a great resource.

My question is, you know, there are some common themes that I’d love for some or all of you to comment on about what the future looks like, right? So, when we think about the themes that all four of you talked about, we can think of diversity and heterogeneity, right? And we can think of needing to include that diversity and heterogeneity as we think about approaches that work for individuals with mental illness.

And I wonder if you — you know, some of you talk more about future visions than others. And I just love to hear any of you who’d like to say something. What do you hope the world of mental health research and perhaps mental health care looks like in another 25 years? I know some of you included that; some of you didn’t. So, I’d love — just love to hear that — those thoughts.

MICHAEL WELLS: I’ll be quick so that everybody has a chance to talk. MM my hope is that we find, you know, treatments for these conditions that benefit all of us. And I think that we’re obviously not there yet. And I think it really starts from the ground up, biologically, looking at the genetics, the cellular, molecular mechanisms, going up to circuits and up to individuals. Making sure that our samples represent the full diversity of the human species, I think, is the only way we can achieve this goal of treatments that work for everybody.

NICOLE PROVENZA: We talked a lot about biomarkers today. And I hope for a future where, you know, like, if you break your arm, an x ray can tell you that the — where it’s broken. And for people suffering with mental illness, I think, a lot of times, they are kind of gaslit into believing, like, oh, it’s in your head. It’s your problem, you know, just like, get over it.

But what if we had biomarkers kind of validating lived experiences, like validating, yes, this is a mental disorder. There is a circuit dysfunction going on in your brain, and here’s what we can do to fix it. I think that would help a lot of people.

ANTONIO FERNANDEZ-RUIZ: So, okay, maybe just to bring up a different angle. So, I think part of the limitation, perhaps historically, in the development on treatments for mental health has been the lack of understanding of the underlying causes. And I think that’s complicated for complex human diseases, but we now have much better technology that only 10 years ago.

So, I do see, you know, the technology is already very advanced. So, now we need to catch up with new ideas of looking at this massive data set that we are collecting, both from the, you know, genomic, atomic point of view, to the functional and imaging. So, we do need new ways of thinking about the data, how we even start to make sense and look for patents in the data that can help us going into the mechanisms. And how can we translate them from, you know, animal models, up to human patients? And that’s a challenging role.

MAURA LANDERS: Would you like to —

BRIELLE FERGUSON: Sure. I don’t have much to add. I agree with everything that’s been said there, and I didn’t talk about this in my talk. But I definitely agree with the approaches that are being used. Can we use the kind of like heterogeneity of these experiences to identify kind of like shared, conserved biomarkers, whether it’s at the genetic level, at the cellular level, at the circuit level, that we can use?

I think we can take a kind of a level higher and say, at the symptom level, what are symptoms that are shared across many of these different disorders? And so, we heard about cognition. I focused specifically on attention, and attention is shared across all of these disease states. So, what can we learn about attention and how attention malfunctions in a way that can inform other behavioral dysfunctions and other diseases?

MAURA LANDERS: Thanks, everyone. It looks like we might have another question. Yes? Over here?

DAVID DELAHUNT: Can you guys hear me? Thanks so much for all your work. I’m Dave Delahunt. I’m an advisor to companies in the in the mental health diagnostics and therapy space. All right. There we go [laughs].

And some companies I’m working with are using epigenetic biomarker technology spun out from Rachel Yehuda’s lab, as well as Dr. Bob Niculescu — you might have heard of — at Indiana University. So, we’d love to hear any your thoughts on the potential for precision medicine.

Most of my background is actually in oncology precision medicine, and that’s been very successful there. And I’m really interested and excited about the potential for advancing precision medicine in in neuroscience and psychiatry. And the, you know, the epigenetic pathway has been very successful for — in the — applied in the oncology field. So, we’d love to hear any thoughts you have on epigenetic biomarker applications. Thank you.

MICHAEL WELLS: Everybody’s handing me the microphone. One thing I didn’t talk about is how, with our villages, we are starting to incorporate epigenetics, so that we’re capturing gene expression and epigenetics from the same exact cell for these assays. So, we are starting to work on that. That’s just commercially available. Those kits are commercially available. We don’t have to do anything special to do that.

Yeah. So, you bring up oncology, which I appreciate it, because there’s many examples of clinical trials being successful in oncology because they either had a molecular or genetic biomarker for either the tumor or for the individual themselves. That would be great to have, I would say, for psychiatry. We don’t really have that.

I alluded to this idea of, if we had a biomarker for drug efficacy, for whatever thing you’re trying to get through the clinical trial, how beneficial something like that could be. Because there’s often clinical trials that fail even though they helped some people. And what inspired a lot of the work we do is a story I read in some — maybe Washington Post or something, in 2017.

It was a story about a drug that failed for fragile X. And what was heartbreaking about it is that some of the families were saying to the doctors, “This drug helped my 15-year-old son speak for the first time.” But because not enough of those cases took place, the drug failed. And they were not allowed to give that drug to their child anymore.

If we had something to identify who would have — whether it be epigenetic or genetic — who would have responded positively to that, it’s unlikely that clinical trial would have failed. And that family might be able to benefit from that treatment. I think it actually spawned legislation around the right to try, even if something is not FDA approved. So, my hope is that we don’t have future scenarios in which people are being given treatments that work in a clinical trial, and they can’t actually take it anymore because of the lack of these sort of biomarkers.

NICOLE PROVENZA: I’m very enthusiastic about precision medicine in terms of neuromodulation as well. I don’t know much about epigenetics, but I know that, like DBS for depression, for example, patients have to jump through many hoops. You know, they fail so many medications, fail expert — like multiple rounds of expert psychotherapy, electroconvulsive therapy, which works for some people, but causes severe like, memory loss and many others, before they can even qualify to get deep brain stimulation.

And so, if we could have, you know, some biomarker that could tell us, like, okay, you failed SSRIs. You know, it looks like you’re going to fail everything else. Let’s skip to DBS. That would help a lot. So, I think accelerating, like the path to finding the right treatment is very exciting.

MAURA LANDERS: Hopefully, we could be talking about that, how well we did it at our 100th, looking back. On that note, if anybody has other things they would like to share, I’m going to give you three seconds, really quickly. Because we are standing between everyone and lunch. So, I’m not getting any eyes. I’m going to say once again, thank you all for your presentations. They’re very informative, leave us a lot of things to think about.

[applause]

Okay. I have a few housekeeping items, and then I promise you can get to lunch. So, before lunch, we ask all speakers and the top — NIMH top five to please remain in the auditorium for an event photo. All participants are invited to join us for a variety of box lunches, which have been provided by the Foundation for the National Institutes of Health.

Please retrieve your lunch from the lobby. You can eat your lunch in the lobby area or the cafe. There are some tables there. Food and drinks are not allowed back in the auditorium. If — we encourage everyone to remain inside the building. I know it is gorgeous outside. I would love to go outside.

Please be aware, if you do go outside, you’ll have to come back in through security. I’ve not been out there. I don’t know what it looks like. But if there’s lots of foot traffic, that could take some time to get back inside. So, just be mindful of timing. I know I’m a few minutes over, so I apologize for time.

Please make your way back to your seats when you hear the time’s around 12:35. Thank you all again for an engaging presentation. I look forward to talking to you all at lunch. I won’t talk your ear off. But enjoy lunch, everyone.

[applause]

Transcript

FEMALE SPEAKER: Thank you for joining us for the National Institute of Mental Health’s third and final 75th anniversary celebration, our symposium, Inspiration and Aspiration: Future Perspectives in Mental Health Research, here at the National Archives Building.

Today’s seating is open, but we do ask if you could please fill the seats down front and in the center to make it easier for people who are arriving, possibly late. In case of emergency, please use the front. Please use the exits at the top of the stairs, near on either side of the theater, and proceed to the nearest marked building exit or follow NARA security and staff for further instruction.

Restrooms and a small cafe are located on this floor outside the theater and to your right. As a reminder, food and drinks are not permitted in the theater at any time. Once again, thank you for joining us today. Please take your seats. Our program will begin right now.

[start of video]

MALE SPEAKER: In the aftermath of World War II, America faced a great and compelling need to address the nation’s mental health. In response, President Harry Truman signed legislation leading to the 1949 creation of the National Institute of Mental Health.

It has been tolerated too long. It has troubled our national conscience, but only as a problem, unpleasant to mention, easy to postpone, and despairing of solution. The time has come for a great national effort.

The National Institute of Mental Health was at the heart of this effort.

For the first time, man now has the tools to explore the living brain.

Today, the National Institute of Mental Health is the lead federal agency for research on mental disorders, supporting discovery across the country and the world. We aim to transform the understanding and treatment of mental illnesses through basic and clinical research to envision a world in which mental illnesses are prevented and cured.

[end of video]

SHELLI AVENEVOLI: Good morning, everyone. Everyone hear me okay? So, I’m Shelli Avenevoli, the acting director — not the deputy — the acting director of the National Institute of Mental Health. I’d like to welcome you today to NIMH’s final symposium in celebration of our 75th anniversary.

Thank you so much for being here today, and it’s especially nice to see a pretty full room here in person and so many more of you joining us virtually online. I also want to recognize that we have two former NIMH directors with us today, Joshua Gordon and Richard Nakamura up hiding in the back.

As many of you know, NIMH is the lead U.S. federal agency for research on mental disorders and is one of the 27 institutes and centers that make up the National Institutes of Health, the nation’s medical research agency. Our mission is to transform the understanding and treatment of mental illnesses through basic and clinical research, paving the way for prevention, recovery, and cure.

Mental illnesses are complex, and they can affect people of all ages, genders, races, and ethnicities. Mental illnesses are the fifth leading cause of disability in the United States, accounting for almost 7 percent of all disability adjusted life years. NIH is committed to overcoming these challenges by supporting high quality research and providing hope to individuals and families impacted by mental illnesses.

The celebration of NIMH is 75th anniversary allows the reflection of historical accomplishments. Over the past 75 years, NIMH has evolved to expand her urgent needs of the nation, while continuing to advance basic, translational, and clinical research to improve our understanding of treatment of mental illnesses. Our progress advances and successes are shared by the Greater research community and the individuals and families impacted by mental illnesses.

It’s really been a true pleasure to celebrate our 75th anniversary in several ways, including our three main symposia. The first one highlighted significant advances in mental research — mental health research over the past 75 years. The second one focused on inclusion and mental health research, disparities in health, and access to care and mental health workforce diversity and brought together people living with mental illness with clinicians and community leaders.

During today’s event, we focus on inspiration and aspiration, very appropriate. We will hear dynamic presentations by rising stars and trailblazers in the scientific community. Presenters will also share diverse perspectives and creative approaches to mental health challenges, including discussions about cutting edge advances that are shaping the future of mental health research.

Thank you especially to all of our speakers today for contributing to this final symposium, and for all attendees who are part of this historical event. So, before we begin our program today, we’d like to hear a few brief welcoming remarks from the NIH Director, Dr. Monica Bertagnolli.

MONICA BERTAGNOLLI: Hello, everyone. I’m Monica Bertagnolli. And I’m honored to serve as the director of the National Institutes of Health. Thank you for inviting me to provide introductory remarks at this important celebration. And I’m very sorry that I cannot be there to welcome you all in person. I’d like to thank Dr. Shelli Avenevoli for your introduction and for serving so capably as the acting director of the National Institute of Mental Health while a national search is underway for the next NIMH Director.

Thank you also to Dr. Joshua Gordon and all the former NIMH leaders who have helped the institute accomplish so much over the years in mental health research. Since I became NIH Director last fall, it has been inspiring to me to work with so many brilliant and deeply committed leaders across the NIH.

I’m incredibly grateful for the powerful team we have put together here throughout all of our institutes and centers to work toward our singular and noble purpose, to improve the health and wellbeing of all people.

Over the last 75 years, NIMH has supported basic and clinical research that has transformed our understanding and treatment of mental illnesses, paving the way for prevention, recovery, and cure.

NIMH research is more important now than ever, given the nation’s mental health crisis as we emerge from the COVID-19 pandemic. With its focused mission, NIMH is well prepared to respond to the growing attention to mental health research across the federal government, in Congress and from the public at large.

I know that NIMH is committed to supporting high quality research and making innovative tools available to help us better understand mental illnesses in all of their forms. And I am certain NIMH will continue to make enormous, if currently unknowable, strides in the next 75 years.

Today’s symposium entitled Inspiration And Aspiration: Future Perspectives in Mental Health Research will feature presenters with diverse perspectives and creative approaches to the mental health challenges that face us today. Research like this provides much needed hope for so many people.

I want to congratulate NIMH for the efforts you made this year to involve the nation in your yearlong anniversary celebration. With multiple public events and conferences and with resources such as podcasts and social media, you reminded all of us of your remarkable 75 years of discoveries and achievements. And you’re inspiring and bringing hope to all of those who work to bring health and wellbeing to all people.

Thank you to all the speakers who are here today to help us celebrate this important milestone and for providing your forward-looking vision of how research can advance to meet the needs of those affected by mental illness. I know that today will be filled with fascinating presentations, and I send you all my very best wishes for an inspiring and engaging day.

SHELLI AVENEVOLI: Great. Thank you. And now it’s my distinct pleasure to introduce our first keynote speaker, Dr. Chyrell Bellamy. Dr. Bellamy is a professor in the Department of Psychiatry Yale University School of Medicine, director of the Yale Program for Recovery and Community Health, and associate director of Diversity, Equity, Inclusion and Accessibility of the Yale Center for Clinical Investigation.

Her research and practice examine sociocultural experiences and pathways to wellness and recovery in the prevention and treatment of mental illness and addictions, peer support effectiveness, organization, and leadership transformation with a focus on anti-racism, cultural humility, and responsiveness, lived experience leadership and community-based participatory research and co-design methods.

Dr. Bellamy openly identifies as a person with lived, living experience of multiple marginalized and minoritized identities, including mental illness, trauma, and addictions. She uses this personal connection in her role as a service provider and academic researcher in the health and behavioral health fields. Please join me in welcoming Dr. Bellamy.

CHYRELL BELLAMY: Thank you so much for that lovely welcome. It truly is an honor to be here. And I also just want to thank my folks from Yale’s Program For Recovery And Community Health, who came down to visit us. And they’re right here in front. [unintelligible]

Thank you so much. Thank you. So, let’s get started. So, my talk today is called embracing lived experience as the future of research. I want to start with a land acknowledgement. All land in the United States was once on native territory. It is our duty to acknowledge that many of the institutions where we work or conduct research are indeed on native land. So, it’s important that we give thanks.

Land acknowledgements do not exist in the past tense or historical context. Colonialism is a current and ongoing process. We need to be mindful of our present participation.

The objectives of my talk today — I will be doing acknowledgements throughout my talk today. I think it’s so important that we recognize all that have gone before us, that have come before us. I know I’m going to forget people, but please know that I am acknowledging you now.

Also positioning, positioning is really important to me to really give a sense of where I come from and — about my journey. I was tasked to talk about my creative process, and so I’ll share a little bit about that. But because a big part of my creative process is the ability to use my — and embrace my own lived and living experiences, I will spend the majority of my talk today talking about that. And hopefully to provide some useful tips that could be really helpful to you.

So, let’s get grounded. There’s a poem that was written by my friend and colleague, Imani Harrington. Imani is a playwright and an activist in San Francisco. And she and I co-wrote a book, plays, monologs called Positive/Negative: Women of Color and HIV/AIDS. I was actually working on my dissertation at the time when I joined her as one of the co-editors.

The poem goes, “We need you, our brothers, our sisters, our people. Help us reaffirm ourselves and loving ourselves. Hold us, we can’t stand because souls of shoes have traveled on our backs for so long. We need you, our brothers, our sisters and our people.”

To me, this this poem grounds me. I say it at everything I do. I say it so much that my team at Yale Perch often say, “Oh no, here we go and again with the poem.” But the poem, to me, is really about, how can we make sure that we figure out how to help people reaffirm themselves and loving themselves.

And particularly for the people that we work with in is doing mental health research. But also, how can we help each other? Because we all need that affirmation.

So, acknowledgements. This woman right here as Dr. Carol Mowbray, who was my mentor at the University of Michigan. She was doing incredible work around mental health research and really looking at ways in which supported education could support people who had a sense of psychiatric illness as they transition back to post-secondary education.

And I actually went to the University of Michigan to do HIV research. But I needed a job, and someone said, you know, “Hey, Carol Mowbray is looking for someone that has experienced working in the inner city.” And I had come from New Jersey, and done a lot of work in Newark, New Jersey. And she needed someone that was ready and willing to go to Detroit, Michigan. And I was like, “I’m ready. I’m there.”

So, Carol Mowbray just really helped me affirm myself. And not only that, I was like, this program is about me. I was one of those students that struggle a lot, you know, when I was going through high school and post-secondary education. And so, for the first time, I felt this sense of being affirmed with research that I was taking part in. Carol Mowbray passed away when she was 57 years old, but she still has a place in my head, and I still go to her quite often.

The woman with the mole is my aunt, Halistine George. She was one of those people that was always reaffirming. Reaffirming about myself as a Black woman, reaffirming of myself as a Black queer woman. A woman that gave me the ability to stand tall, and no matter how I showed up. And Halestine also died at the age of 57.

I am 57 years old. And so, it means a lot for me to be able to stand here today and be alive and feel happy about being alive for the first time in many, many years. The woman down in the bottom, obviously, that’s her when she was cute and 18. That’s Dr. Alfrieda Daly. And Dr. Daly also passed away, but she died when she was 93. So, that gives me hope.

And Alfrieda was a person that I met at Rutgers when I was getting my masters in Social Work. And she overheard me advocating for myself. And she approached me, and she was like, “Hey, you did a good job advocating for yourself. Come work with me on this methadone HIV related project.”

And from that day, Alfrieda stayed in my life. She came down to South Carolina with me often to visit my family. She went to fish fries and all sorts of events that my family held over the years. But she also was a person that said, “You should go to graduate school, and you should go to the University of Michigan.”

And I was like, “University of Michigan, what is that?” And I thought they just did basketball. And, you know, never did I know that, you know, she was sending me to one of the number one universities in the world. And it was just really important for — to have Alfrieda in my life. So, thank you to all of them, and to all of the women people, non-binary people who have lifted me and continue to lift me. Ashay.

So, where I come from? I come from South Carolina. I’m from a little town called Brooksville, Little River. It’s all now known as North Myrtle Beach. And we are of the Gullah Geechee people. And this is our land. If you are familiar with the South Carolina, you’re used to seeing the mosque growing on the trees. And that’s the Gullah Geechee flag there.

And I mentioned that because that culture grounded me again in who I am as a Black woman. These are more pictures from the South Carolina area. Atlantic Beach is the beach in North Myrtle Beach that only Black people were allowed to be on that beach. Because Blacks were not allowed on the other beaches in Myrtle Beach to go to those beaches. So, still today, when I go home to visit my mom and my family in Myrtle Beach, I make sure that I touch the sand of Atlantic Beach. It’s called the Black Pearl.

And then we journey up north, like many of our folks did, from the Myrtle Beach area up to Trenton, New Jersey. And Trenton, New Jersey is where I grew up, where I attended public schools. And again, where I gained the sense of myself by growing up in a predominantly Black area, had predominantly Black teachers. And it helped me see that there were other people like me that are achieving and achieving successfully. But as they say, Trenton makes the world takes. I’m sure you’re used to seeing that on the train.

So, changing the discourse for many years, I was not out about my lived experience. But being a part of Carol Mowbray’s work really gave me a sense of it’s important that people step out and step into their own lived experience. That’s me when I was five years old. And that’s me with the hat on at the University of Michigan. That’s me and high school, that senior year picture.

And I want to talk a little about this article in The Michigan Record. When that article came out, it came out because the University of Michigan was doing a film called Depression on College Campuses. And they asked me to be a part of the film to talk about my lived experience. This film was shown at the university — at the Michigan theater in downtown Ann Arbor. And it was a wonderful success.

After the film, one of my colleagues came up to me and he said, “You know, I spoke to, you know, one of our professors. And he said, you know, our career is ruined.” And I just kind of looked at him. And at first I was like, taken aback, but then I was like, “No. Actually, it’s just starting.” It’s just starting, because I’ve received so many calls of people who are reaching out to talk about this. So many professors, so many students, so many community members who want to talk about their lived experience. So, to me, that is the start of my career.

I also realized that that person, the reason why he said that is because he also was a Black male. He came through academia at a time when we all were supposed to act a certain way in order to make it through the system. So, again, he was just giving me that sort of warning that I need to be able to learn how to walk light so that I don’t tread in ways that I shouldn’t.

But again, being myself, I stepped out and did what I was supposed to do in regards to lived experience. And the reason is based on this quote by Audre Lorde, which I’ll read to you. “Survival is not an academic skill. It is learning how to stand alone, unpopular, and sometimes revolve. And how to make common cause with those others identify as outside the structures in order to define and seek a world in which we can all flourish.

It is learning how to take our differences and make them strengths. For the Master’s tool will never dismantle the master’s house. They may allow us temporarily to beat him at his own game, but they will never enable us to bring about genuine change. And this fact is only threatening to those who still define the master’s house as their own source of support.”

And why is any of this important? I threw this slide in here because I think it’s important to acknowledge that so many Black and brown individuals are — continue to die because of suicide. We have a photo of Dr. Candia-Bailey, who was a professor and passed away due to suicide. We have Kryst, who was Miss USA, who also died as a result of suicide.

And then we have two of my colleagues, one is Elias from Brazil, who visited us as a visiting scholar. Amazing energy. He was there. And then November, just only three months after he visited us, we found out that he died as a result of suicide as well. He was a brilliant nurse in academia.

And then we have my colleague from Yale’s Program for Recovery and Community Health, Dr. Miraj Desai. Dr. Desai died last November 3rd, I believe. And he’s done some amazing work. He had a K Award. He had just submitted a DP1, I believe, the day before he passed away.

So, it is important that we nourish each other in academia. It’s important that we recognize and acknowledge that so many of us are going through things, and we may never talk about those things. But yet we continue to struggle and try to get that DP5 in and try to get that RO1 that check in on people, right? So, that’s my message for this.

So, my creative process. Someone asked me — you know about nerves? I tend to get nervous all the time when I’m giving these types of talks. 80 percent of time I vomit. I didn’t vomit today, though. [laughs] And so, I have this technique called palms down. And basically, that means panic at the last moment. You know, it was hard with this one, because as soon as Dr. Gordon sent me the message, and was like, “We want you to present.” I’m like, “Oh.” It started coming right away, right?

But it’s really important because if I don’t, then I spend so much time and energy focusing on the what, instead of really just embracing and sort of embracing that it’s okay for me to be proud. It’s okay for me to take this in. And don’t get so caught up in the words and the language of what it is that you’re trying to do.

Learning from and embracing community and lived experience, mine, and others. It’s those folks down here that I’ve worked with since I came to Yale’s Program for Recovery And Community Health, Kimberly guy and Richard Youins. I talk to them practically every day of the week. And they inspire me. We go to I go to them often with any idea. They either shoot it down or, you know, they give me advice on how to improve things.

And I just think it’s really important for me because that gives me a sense of purpose in this work. And that also goes with remembering my why. Why is it important that I do this work in the first place? That why might change depending on what it is that I’m doing that research. We’ll talk a little bit about that later.

Daring me to dream is critical. So, I remember early in my career, people would say, “Oh, you can’t study,” only Black people. Because people will not allow you to do that. You have to have a comparison group to other, you know, to whites. But I kept asking why, like, why is that the case?

And so, my thing with this is, don’t question the why — or question the why. But the question should be, what does it take to make it happen? What do I need to do to convince you that this is the research that I want to do? And seeing it all as a creative journey, as Dr. Shelley Best would call it, it’s a creative disruption, the work that we’re doing.

Revolutions begin when people who are defined as problems achieve the power to redefine the problem, John McKnight. We each have the power. This is one of those quotes at Yale’s Program for Recovery And Community Health that we use. I am privileged to now be the first director of Yale Perch, after my mentor, Larry Davidson, in 20 years.

I’m also proud to say that I am the second Black woman in the Department of Psychiatry in its history to receive full — to become full professor. And again, it is those experiences that I think it’s important that I say out loud, because there’s so few people who have been able to even get in the pipeline.

So, consumer involvement, user involvement, lived experience involvement, has been an increase in priority across our federal landscape, at least since 2002. We’ve added, you know, peer support. We’ve added, you know, the involvement of consumers — and that’s the word that we used to use, or service users in all, you know, aspects of work.

In terms of research, we do it, but we don’t do enough. Like there’s — while there’s a continuum of ways to involve people with lived experience. It’s usually just to help with recruitment, or just to have your, you know, quarterly advisory groups, because that’s what you told NIH that you were going to do.

Key to involvement is community based, participatory research, which I’m sure all of you know about. But I really want to focus on two aspects of this because it’s really about bringing the community together so that they are assisting throughout all aspects of the research. From conceptualization and that is generating the ideas to data collection, to design, to analysis.

And people often say, “Well, how can they do analysis? They don’t know statistics or they don’t know qualitative methods.” Then teach them, right? Teach people how to do those things. And there’s so many ways that we can involve people, particularly as well in terms of dissemination. Co-learning is very key to that process. And co-learning means a strengths-based approach that acknowledges privilege and power. And again, those are hallmarks of CBPR.

I’m now going to go through a few slides. And I’m going to go through them rather quickly, because I’m just pointing out, again, some of the history around the involvement of sort of patients, clients, state talk, stakeholders. Today, we’re using more of the terms lived and living experience experts and involvement and research. This goes back to the 1980s.

I actually was part of that process, as I mentioned, having done work in the area of HIV/AIDS. We were doing a lot of that work back then. I fear to say I was one of those gatekeepers when researchers would come to me, when I was the assistant director at the New Jersey Women and Aids Network to try to get research projects going. I would give them like a thousand questions of, why are you doing this? Why do you want to meet with our people?

So, we have Rose Kushner, who did some freelance writing and talked about breast cancer and surviving breast cancer. Lots of work around activism, again, AIDS and ACT UP, and groups like that. Maternal health, again, more work was done in that area. And the United Kingdom and Canada, I can say arguably, that they have one of the best systems of really engaging patient provider involvement throughout all aspects of their work. And it’s more of a mandate.

Over the years, PCORI has been instrumental in making sure that the target population is also key to that research and hired as partners in the research. And I’m thrilled, thrilled, thrilled, as a late to see that NIH across the board, I’ve seen RFAs that are asking for more lived and living experience involvement in projects.

So, why lived experience research? And I want to start with this first one. Rather than presume or guess, just ask the author. And actually, that’s a phrase that Kimberly Guy uses all the time, which is, if you want to know about the book, ask the author, you know. Don’t just — you know, go to the people that have the information. It gives us a connection with that human experience. And that’s so key when we’re talking about the future for research.

Because as we focus on future research, we’re bringing in all sorts of mechanisms like AI. So, we have to make sure that we continue to make that connection with the human experience. It also gives us rich stories that go well beyond the data, particularly if you’re coming at this from a quantitative perspective. And it reminds us that illnesses happen to people.

Another aspect of this is that it helps us in terms of bridging different communities. I love when I’m doing research projects, and I have the doctors in the room and the RAs in the room, and also, you know, people with lived experience. All coming from different walks of life to come together, to really figure out and solve a problem together and bring all of their resources and all their experiences. It just asks for a more rich learning environment.

It also allows us to address discrimination and other issues that sometimes are like, you know, we tend to hide in these situations. But working with people with lived experience, they have a way of bringing the issues right out and calling us on things that we need to be called out on.

Otherwise, include can we move away from just this illness model and really include, you know, things around the social determinants of health and other ways that people are, you know, living in these environments.

The other thing here I have is more honest responses from participants, and this is really key. I know that when we were doing a research project, we have all of our lived experience researchers examine our measures. And sometimes when they’re examining them, they’re like, “This doesn’t even make sense. Like, this question doesn’t make sense.” And I’m like, “Well, you’ve been to lots of studies. So, you’ve probably heard that study — I mean, that question a thousand times. And they’re like, “And I probably didn’t answer it right a thousand times.”

And I think that’s really important to know. It’s really important — I know that we have these standardized instruments, but we also need to make sure that they are standardized based on what human beings are telling us makes sense to them. Otherwise, we’re collecting data on questions that people may not even understand what you’re asking them.

And particularly, we tend to get these satisfaction surveys. I mean, I don’t know — and I can tell you, primarily in our state, in Connecticut, satisfaction surveys are like, really, really high. Most people are saying they’re, like, totally satisfied with everything. But then if you go talk to them, they always have some complaints about this, that and the other. So, how can we learn to collect richer data? More wise, better recruitment, getting the people that you need.

I have a project right now. It was originally funded through the NIH Common Fund, and it’s called the Imani Opioid Faith- based Breakthrough Project. And the thing I love about this project, in terms of recruitment, is that we have to go where people are. And when I say we have to go where people are, we do these deep dive recruitment efforts, where we’re going in alleys, where we’re going in places where no one else will go to have conversations with people about the projects that we’re working on.

And I think this is really essential that if we want to really reach the people, we can’t keep calling them the hard to reach population. Hard to reach to who? Only to us. The people in the community know how to reach these people. And here are just a few examples of those type of articles that we been able to publish as a result of some of this great work.

And as I mentioned, Kim is saying, if you want to know about the book, ask the author. We actually use that as our title for this for this paper. This paper was again led by Dr. Desai. Again, we miss you, Dr Desai. Another paper was led by another young researcher, Ana Florence, with a whole bunch of us.

Here’s the thing about lived experience research and doing sort of co-production and co-design work, it’s so important to also acknowledge all of the people who have been involved in those research projects. We acknowledge people with lived experience. We acknowledge Ras. Everyone needs to be acknowledged for all the work that they’re doing.

And so, a host of us are on this paper. During covid, we wrote this paper because many of the people talked about, you know, they were being approached because they have lived experience. Like, how — you know you’re surviving this better than most of us and can you tell us how you’re doing that. So, we had a series of conversations, and we wrote this when reality breaks from us, lived experience wisdom in the covid era.

Another one is by colleagues, Louise Byrne, Larry Davidson, and others. Louise is from Australia, to disclose or not to disclose. Again, talking about the central aspects of lived experience. Because disclosure, you know, I can stand here proudly and talk about my lived experience, but I will say that it’s a journey. It’s a constant journey of coming out about your various different lived experience, and it’s not easy. And this paper actually points to some of those factors. Again, all driven by lived experience and actually by lived experience researchers.

Another paper, which I just love the title That was a State of Depression by Itself Dealing With Society: Atmospheric Racism, Mental Health, and the Black And African American Faith Community. Dr. Desai and us, we worked with churches to get a sense of how do you even define those experiences that you have. They were not using the term depression, they were not using the term, you know, bipolar or schizophrenia. They were using other terms. So, how, if we’re trying to work with particularly the Black community, how can we define what it is that they’re calling those experiences.

And another paper that we work — we wrote, and I have Dr. Jonathan Edwards right here in the front, and this is a paper on surviving race with allies, disability, race, ethnicity, and human rights. And actually, this is for a chapter. We lost Celia Brown, who was an activist, just recently.

So, I want to quickly walk you through an example of this process. Everything that we do, we do it from a place of starting with the why. I don’t know if you know Simon Sinek’s TED talk on starting with the why. But basically, Simon talks about it’s really important to focus on the why. Because when you focus on the why, then you focus on the passion. What draws people into this work in the in the first place?

And when you’re working with community and researchers and lived experience and RAs and, you know, a variety of different people, while people are excited to come together, they will also get very bogged down in the work. Particularly when there are conflicts. There might be conflicts coming from the lived experience side of things and say, “You know, I realize that you’ve been doing this for the last 20 years. But we’re telling you that you should probably think about doing it a little differently.”

And then, you know, so there are arguments on both sides. So, how can we do that and hold on to that why. By holding on to the why in your own passion, that’s how you’re able to hold on to the work.

And so, here’s a why that was central to a NIMH grant. We have an R34 which we called Harambe, which are folks down there name. And it means, let’s pull together in Swahili. And it was really a project that focused on, how can we, you know, really look at the fact that people with mental illness are dying 25 years earlier than the rest of the population.

Every time I say that, though it feels criminal to say it and not do anything about it, right? So, but how can we do something about it? And that is the thing that drove us that were in that particular study. That was our why. How can we make sure that this doesn’t happen? That was our collective why.

So, in order for that to happen. What do we need? So, the how engaging all of us is key. And when I say all of us, we all have stories or barriers and facilitators to healthcare. We were hearing from the doctors talking about their barriers and facilitators to healthcare when they go in as patients. It was awesome for the people with lived experience to hear them also talk about their experiences.

Because they thought for some reason that they had a gold card, that when they walked into the medical facilities, that for some reason they got treated differently. But it doesn’t work that way. We also got to hear from RAs right, research assistants. Oftentimes, research assistants are like at the bottom of the wrong and often are not counted on or talked to about their ideas. But in this project and this work, we want to make sure everyone was included and that their voices were being heard. And I think that’s central to making sure that you get great results.

Inclusion, partnership, and transparency. What’s really key for all the work that we do is entering and exiting communities respectfully. I don’t care whether that is the local mental health system. I don’t care if it’s someone’s home, someone’s neighborhood, that we are only there as visitors, and then we will be leaving.

So, that space doesn’t belong to us. And just like you know, I guess, because I’m a Southerner, and when you walk into any southerners — particularly a Black southerners house, the first thing that you do is acknowledge the elders in the house and make sure that you say hello, right? And I’ve been in so many of these centers where you can walk through them and you can walk out and never have had anyone not say hello to you at all. Right?

So, it’s really important that we acknowledge that people work in those communities, that that’s their lives, people work in those agencies. And key to that is relationship building. One way to start building relationship is to acknowledge the people who are there.

Transparency. Can we be — can we really be honest with each other, and are we willing to learn from each other? We know that that’s not going to happen in day one. I mean, trust is the automatic — you know, lack of trust is an automatic, you know, default for many of us. Particularly if you’ve had any, you know, experiences of trauma or you know, we know that it takes a long time to build up that sense of trust.

But ways that you can do that, one is again, talking about positionality. Talking about who are you and why are you here? Asking appreciative questions. Turning things around and asking questions of what works. Don’t get so bogged down in the problems. Because we get bogged down in the problems, we’re never going to solve anything.

And breaking it down, translating discussions on research and in a language that we can all understand. I tell my entire team that if Chyrell’s mother doesn’t understand, then forget about it, right? And I think it’s so key. And I say that because when I call my mother and I talk to her about research, and she’s not able to understand, I need to talk to her in a language that she’s able to understand what I’m trying to say.

And I don’t think — I think we all need to do that. What’s the purpose of writing these, you know, articles and, you know, doing this work, if your everyday person doesn’t have access to it and can’t understand the language that you’re trying to, you know, impart.

Fostering understanding and mutuality. It has to come with the willingness to keep the discussions going, even when they’re tough. And they will be tough, there will be times when they will be tough. I think about that even from the — I’ll talk about from my experience. You know, it’s humbling when a person with lived experience, or a person in community questions you and your direction.

It doesn’t mean that I, you know, don’t show up with all of the knowledge and all of the experience that I have as a person with a PhD and all of my research accolades. I show up with all of that. But I also have to be able to have those discussions with, you know, people from all different sides. So that we all can come to an understanding about what it is that we’re trying to talk about.

A willingness to listen, revise and adapt, right? So, often we get caught up and you know those check boxes? Oh, you know, you have your checklist. I did this today. I did that, I did this. But sometimes you go checking too fast, right? And one thing I will say about doing participatory work in any form is that it will take more time than anything else. And if you don’t make the time, then you’re not doing it properly. I already mentioned entering and exiting and the willingness to partner is just key, and validation of each other’s roles in this work is also key.

So, opportunities to take action. Here, I just have a few of — discovery, dreams, design, and destiny are terms from Cooperrider’s appreciative inquiry. And really those questions of, what gives life? You know, what is giving your — you life, but also, what is giving life to this research. What might be envisioning results? What should be the idea like, how can we co construct this together? And how to empower, learn, adjust, and improvise?

Again, constant throughout the process, right, being flexible. I know you wrote in there and your, you know, specific aims that you’re going to follow this, that, and in the other. But also, be flexible, so that you can learn and grow and revise and adapt along the way.

And then I just want to end with these questions. What are you currently doing in your community to enhance inclusion? What more might be done to build community? What might we do collectively to advance community? If we stay focused on the why, we all get something from the partnership. In that particular study around Harambe, we all learned about what was happening in terms of health choice and health outcomes for individuals with mental illness.

We improve health outcomes for those individuals. We improve services based on what it is that they’re asking for, rather than just going about in our own way. And we have informed research that is coming from person centered perspectives.

Participatory approaches and the need for leadership. Today, again, the language that we are using is called co-production and co-design, leadership and also knowledge equity. And this is so key to how we think about and do this work.

At the Yale Program for Recovery, we started a consumer research and evaluation network probably over 20 years ago. We called it CREN. And CREN was really about bringing people together so that when a researcher had questions, they could call up a CREN. And then a CREN would be able to provide them resources that they need, particularly lived experience Resources.

Today, I’m proud to say that we’re moving toward what we’re calling the lived experience experts as partners, LEAP initiative. And that, again, is bringing in more people who can focus on lived experience research. I also just want to acknowledge that I’m certainly not the only person that has done this work. We have lots of people who are doing great work in this area.

I have colleagues such as Nev Jones, Laysha Ostrow with Live & Learn. And I mentioned Peggy Swarbrick, all lived experience researchers like myself who make sure that this is key to the work that They’re practicing.

In closing, in embracing the future of research and involving lived experience — lived and living experience. And I keep saying lived and living experience, because right now, we are — it’s so key that we make sure that we’re talking not only about the people who have lived it, but the people who are currently living it.

Those people may not even use some of the language that we’re talking about around recovery, around harm reduction. They may still be struggling and in and out of hospital or in and out of using drugs or choosing to continue to live the lives that they live. We have to make sure that we hear from both people with lived and living experiences and invite them in the partnership. It can’t be just the people who we think are, well enough, you know, to be at the table.

In terms of research in this area, we do need more research in this area, there’s a lack of systematic evaluation regarding how lived experience expert partnerships translate into improved health outcomes and reduced disparities. So, we need more research in this area. Existing frameworks often fall short of providing clear operational guidance for involving LEEs in meaningful, non-tokenistic ways.

How can we make sure that they’re involved throughout in the variety of different roles? Key questions include, how does partnering with LEE happen so that people across all levels or skills or expertise feel valued. It’s that subjective feeling of feeling valued and being a part of the process.

How do invest investigators incorporate these values in their research? And how do we know the authentic engagement of LEE in research is happening across different contexts, different cultures and populations/ As we have learned over the 25 years of doing this type of work involving LEEs again.

I’ll just say it again involves commitment. It involves time, resources, humility, sensitivity, a genuine desire to learn from one another. And most important, the ability to develop authentic relationships that build on mutual trust and respect. If we all had that, I think we could all go home at the end of the day and really feel like you could take a good nap, right?

And actually, I will say that actually — when they were asking me again, like, what is your creative process? That is my creative process. Because it starts off in the morning, talking to people that I love, that I love working with about research, about what’s up for today. And then ending it and knowing that we’ve done our best for the day.

Those relationships are not just part of the process. They are the process, right? They are the process. It’s so important that we make it a part of the process. And of course, make sure people get paid too, right? And in closing, the future, research needs to develop rigorous, psychometrically valid measures that can capture the multi-dimensional nature of lived experience, expert partnerships. And again, that’s cross diverse populations, diverse research contexts, and ensure that it’s authentic and inclusive.

And I just want to end here so I can open up questions. But these are two of our projects and two of our amazing research teams. First is the Imani U01 that I have with Dr. Ayanna Jordan out of MIU. And these are folks here in Connecticut, and they’re just beautiful faces. And the folks here, I actually have a Brazil Peer Implementation R34 grant where we are trying to implement peer support in the city of Campinas.

And these amazing folks have been meeting for the last year to learn about research, to learn all about peer support. They’ve adapted a peer support intervention and made it their own. They showed up. You know, obviously there were language challenges. I got a chance to visit them in May with Dr. Mark Costa over there. And it was just a tremendous experience to also just hear from them about how much they felt valued as being a part of the research team with Dr. Rosano Maco Campos [phonetic] over there. So, again, you can see this big smile on my face, because, you know, they just bring so much joy to my life.

And in closing, you belong. For belonging to be real, people need the recognition of others. A message given in word, deeds and attitudes that says you do belong. You are a valuable member of this community, and we need you. Thank you.

I’m not sure if we have time for questions, but I wanted to make sure that when we did end, because I know we’re doing a lot of transition, and that presentations are back to back. That people had time to talk, but questions?

MALE SPEAKER: Yes, hi. So, thank you very much. That was really fantastic and inspiring. I wanted to really make just two comments. I think a lot of attendees are probably not aware. So, I’m in the peer review branch at NIMH. So, we review a lot of the applications that come in that are sort of a specialized initiatives, and RFAs and whatnot.

And I think the point I wanted to make, which I think really follows up on what you’re saying, is that, first of all, we’ve seen a very large increase in the number of applications that include community based, participatory research. And so, I think that’s inspiring, and it certainly is consistent with the level of importance it takes.

The other point I thought would be worth making is that, you know, our study sections, which include — they focus on effectiveness of mental health interventions and also mental health services research. Again, something many of you may not know is they have built into them what are called public reviewers. And these are individuals with their people with lived experiences. They often have worked or do still work in community health clinics, at foundations, at advocacy groups.

And they are — like we have standing members of these panels that are such individuals. And it’s very clear that they bring a profoundly valuable real world perspective. That I think the scientists understand a lot of these issues, but they sometimes get a little bit bogged down in the design of the studies and whatnot and lose track of the practical realities.

And so, I guess my point is, NIMH, I think is definitely making efforts both that are inspiring applications, and then also in how we evaluate them. Thanks.

CHYRELL BELLAMY: For sure, for sure. And I haven’t served on the standing review for NIMH serve for two years. Shout out to Eileen Schultz [phonetics], who was just an amazing person. I just want to say that, you know, I love it when those folks are in the room. Because they always offer, you know, just get right down to the, you know, the plainness of it all and just pose these like, great questions that we all can think about. So, yeah, I love that you do that. Keep doing that. That’s awesome. Yes?

FEMALE SPEAKER: It’s very inspiring. I’m a researcher from [inaudible] program. [inaudible] I’ve been trying to involve lived in and folks with living experience, but it’s been difficult. One, because, you know, you have to know how to include them and build capacity before you get [inaudible]. Otherwise, that’s the [inaudible]negative consequences.

Plus, also this kind of approach that they don’t know something. Whereas I’ve tried to build capacity within our team, to engage them in appropriate ways first, and build capacity and try to get them to the people. Any suggestions for building capacity [inaudible].

CHYRELL BELLAMY: First of all, give us a call. [laughs] And you can talk to some of our folks down here. I think that — I don’t think we should over sort of inflate what capacity means, and just really think about inviting people to the table, right, first. To have conversations about the research itself, about what it is that you’re doing. And maybe focus on — even if you have to do that several times, like three or four times, until everyone has a good sense of what it is that you’re trying to study here.

And I will say that that’s not just important for people with lived experience, though. That’s important for the RAs on the team. That’s important for other people on the team too. Because, you know, the PIs, you know, you write the grants and you have, you know, you know it in and out. But most people at the table actually don’t know it in and out.

So, I think we all need to slow down and break it down so that we can explain it to everyone. Now, in terms of building capacity, there are so many things that you can do like for us, like take qualitative interviews. Like, if we wanted folks involved in qualitative interviews, we first might start off by shadowing right? So, having them shadow me while I’m doing a qualitative interview, have them in a room where we’re doing like qualitative analysis.

But again, giving them some of that same training that you would give any new researcher, you know, postgraduate student who’s coming to work with you and having and taking the time to do that. Because one of the things you mentioned about like that, you don’t want to further like sort of increase, you know, disparities, right? Or make people feel sort of, sort of less than because they don’t know certain information.

Larry Davidson used to have his daughter when she was young. She’s now that — she now done the intern with me over the last two summers. But when she was, like 10 years old, she made signs for us. And basically, it was like stop signs that said, break it down. So, in our staff meeting, if someone said something, you can hold up the sign to say, “We don’t understand what you’re saying.”

And I think again, that was important, because in our staff meetings, we have people come from all over the world. And they have — they’re talking about a variety of different science related topics. And I study social science, so I may not know exactly what they’re saying, sort of in the neuroscience area. But often, we just sit there and we’re like staring, and we don’t even know what the heck people are saying, right?

So, again, breaking it down allows everyone to say, “Let’s step back a bit so that we all can make sense of this material together.” And I think that that is heartwarming for other people, that it’s not just the people with lived experience that need this information and need to have it broken down, but it’s all of us, in some ways.

MALE SPEAKER: A great presentation. Congratulations. I’ve had this burning questions that I’ve been at Perch. And I’m glad I’m in the house so that I really present it and say it. And try to get some really solid understanding of exactly what’s going on here. I mean, research, I think, is needed. It is designed to make our lives better.

But what I’m considering, I’ve always thought about is sustainability. So, you know, we have gotten people to participate in the research. We’ve gotten people that we’ve seen their lives really blooming and get better. And so, knowing that this is funding by, you know, you guys here. And I don’t see why other government agencies that you’re not coinciding that with the research and research information to sustain it within communities, if it’s really, truly working.

I mean, what good is research? What good is discovering it’s something that [unintelligible] somebody life if it’s only for two years or four years? I mean, I’m not the sharpest knife in the drawer, but damn. [laughter]

So, that’s always been my issue with a lot of grants that we’ve done. And I’ve witnessed this. I’ve seen people get clean. I’ve seen people lives change and get their kids and they’re growing and their kids are in school. And I’ve seen folks really get it back together, you know, and get on their medications, and come back out in the community.

And at Perch, we got so many things going. We got a bigger group. We got, I mean, there’s so many things that people connect with and feel up into being a part of, you know. So, it’s — but it’s two years, and after two or four years, or three years it’s done. And it’s like, you know what it reminds me of? And my surgeon, this guy who did my hand, told me, he said my hand is so bad. It’s like a house that’s burned down.

But after you come in our community, you do your research, you get our information, and then we you give us a little, small stipend, and then you leave, and it’s like a burnt house with the train still up.

CHYRELL BELLAMY: Thank you. Yes, sustainability is key. I’m not sure. Maybe someone from NIMH can speak to whether or not you — you’re now putting in a sustainability statement. I know that when I was talking recently, actually last week, to a PO from NIDA [phonetic], she mentioned the acronym SPECS. And one of the S’s stands for sustainability.

And so, now you have to complete a form stating how you actually will sustain this work that you are proposing. And so, I — that was new for me, hearing about this particular form. I think that’s a wonderful idea. I think it’s a wonderful idea because, you know, I get the pleasure of working with this young man, Richard. And, you know, and if it wasn’t — if I didn’t have him in my ear of how can this be sustained, I probably would just say, “Okay. Here’s my — I did my analysis. I published my paper. Now it’s time for me to write the next research grant, right?”

But instead, you know, Richard and the other people on the team will say to me, “Nope. Let’s figure out how to then take this information and take it to the community. So, after you know Harambe, we then approach the city, — the state of Connecticut. And we were able to do three Harambe groups at local mental health in Bridgeport and Middletown, as well as in New Haven. So, they were able to see what does this look like with just people doing it in the community. And that was a great opportunity.

Again, it’s important that we continue to try to focus on how can we sustain this work? Because if we don’t, then we run — we are truly doing the disservice for our community. And we might, in a sense, be further increasing some of those disparities. Because people get to a point where they get start trusting in you. They see some improvements in their health. And then you kind of pull away, because the research is over, right?

So, we got to make sure that once we get this research done, that you know, we’re doing some translational activities. And then making sure that, you know, our agencies, our mental health agencies, our substance use agencies, our communities are really embracing the work. And then, you know, using our findings to do these programs. So, thank you, and thank you very much. One more question. Sorry.

FEMALE SPEAKER: Morning. Thank you for your talk. Cognizant of the time, this actually relates to what the gentleman before me said. So, we have some research that is traditional and it takes from the community. We have some that’s transactional. If you give to me, I’ll give you something I determine. Yours is more participatory, is more collaborative and relational, which I appreciate. But I’m curious, what did the individuals that you’re with, that you’re co-producing with, ask of you when you came to them?

CHYRELL BELLAMY: Wow. For me, individuals are asking for the honesty and transparency from the beginning, right? So, they want to know exactly how this works. And I say that because recently I was involved — I do this in various different projects. And several of us are in another project that I’m not the PI on.

And I noticed that, you know, we were in a separate meeting than the research team. And I said, “Why are we separated?” And they said, “Oh, it just makes it easier, because we don’t want to bore you.” I said, “Who says they’re going to be bored?” Like you just made an assumption that other people are going to be — because they have lived experience, that they’re going to be bored. I said, “Actually, I bet the people that you’re talking to, are probably bored. You know.”

But I mean, I say that because I think it’s important that they’re included in all aspects of the research, right? So, that they understand it, that they trust, that I’m not just using them. One of the things that they often want to make sure is, what do they get from it, you know? And often, that involves for them, they want to make sure that they got trained.

They loved all of the training from human subjects to HIPAA to learning about the different measures, to qualitative analysis, quantitative, you know, all of the different aspects. And also learning about health disparities in our communities, right? So, this is something that we all study. We know what the health disparities are in Black and brown communities. But when you are a person that has lived experience and you’re just you might be just hearing it for the first time, it’s also giving up my time to be able to talk to someone, even after the meetings, to say, “Chyrell, you mentioned this. Is that for real? Black people really are dealing with that?”

And just being really able to have those conversations that they may not be able to do in the room from the beginning, right? You know that also takes time, right? So, yeah, thank you. That’s a great question. I really appreciate that. And thank you all so much.

75th Anniversary

Overview

In celebration of its 75th anniversary, the National Institute of Mental Health (NIMH) is hosting its third and final symposium, “Inspiration and Aspiration: Future Perspectives in Mental Health Research.”

This symposium features dynamic presentations by rising stars and trailblazers in the scientific community. This exciting event offers a unique opportunity to explore diverse perspectives and creative approaches to mental health challenges. Join us for a day of enlightening discussions about the cutting-edge advances that are shaping the future of mental health research.

Registration

This symposium is free, and registration is required for both virtual and in-person attendance .

• In-person attendance will be limited, therefore, any requests for in-person attendance after the event reaches capacity will be placed on a waitlist.
• If you are unable to join in person, a virtual option is available.
• A recording of the event will be posted on the NIMH website.

Contact

For logistical or programmatic questions, please email the event organizer at nimhcelebrates75@mail.nih.gov.

More information