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NHLBI - National Heart Lung and Blood Institute

Project Summary Dr. Shah is a clinician-scientist with a focus on cardiovascular disease (CVD) heart-brain mechanisms and digital biomarkers, aiming to address the critical intersection between psychological stress and autonomic health. This K24 Mid-Career Investigator Award will support Dr. Shah in expanding research on sympathetic nervous system (SNS) activity and its role in both CVD risk and mental illness. This award will also provide resources to mentor junior clinical investigators and public health students in these areas. It will also provide Dr. Shah with the necessary training in advanced signal processing and analytics to work collaboratively with his various engineering collaborators. Dr. Shah has a strong record of mentoring trainees and contributing to cardiovascular research programs at Emory University, including the NHLBI-funded T32 training grant on cardiovascular health disparities. The mentorship component will focus on the design and execution of patient- oriented research projects in stress physiology and wearable technology, as well as on fostering independence in trainees pursuing careers in cardiovascular research. The study will leverage ongoing studies including Smart Health and Rehabilitation Technology (HEART) which will involve enrolling 300 veterans in cardiac rehabilitation and the Myocardial Infarction and Mental Stress 3 (MIMS3) cohort (R01 HL109413), which includes 306 post-myocardial infarction (MI) participants who underwent mental stress provocation with ECG monitoring and long-term follow-up. Specifically, Dr. Shah and his engineering collaborators will perform innovative analysis of the multi-channel ECG to examine periodic repolarization dynamics (PRD), a novel ECG-based biomarker of SNS activity that measures the low frequency spectral power of beat-to-beat changes in the spatial T-wave axis. The specific research aims of this project are: (1) to evaluate changes in PRD in response to mental stress and after therapeutic lifestyle modification; (2) to assess the association of PRD with mental health conditions, including depression and post-traumatic stress disorder (PTSD); and (3) to examine the relationship between PRD and long-term CVD outcomes, such as heart failure, myocardial infarction, and CVD-related mortality. This award will enable Dr. Shah to continue developing innovative research on digital biomarkers and autonomic health, while strengthening the mentorship pipeline for cardiovascular research. This will ultimately contribute to preventing adverse cardiovascular outcomes through both scientific discovery and the development of future investigators.

NHLBI - National Heart Lung and Blood Institute

PROJECT SUMMARY Overview. This K24 Mid-Career Patient-Oriented Investigator Award application proposes to support mentoring of junior investigators to apply implementation science to improve TB treatment outcomes and reduce long-term TB-associated disabilities among persons with and without HIV, with direct relevance to U.S. TB programs and high-risk populations. Candidate. Dr. Davis is a clinical epidemiologist and practicing pulmonary/critical care physician, Director of Educational Programs at the Yale Center for Methods in Implementation and Prevention Science (CMIPS), and Associate Professor of Epidemiology and Medicine at Yale University. His research develops and evaluates innovative strategies to improve TB diagnosis, treatment, and prevention in settings where HIV is co-prevalent. He conducts observational, mixed-methods, randomized, and quasi-experimental studies in the U.S. and internationally. Dr. Davis has been continuously NIH-funded since 2006 (F32, K23, and multiple R21, R01, and D43 awards) and has authored >170 peer-reviewed publications, including >60 as first or senior author. He has mentored >50 students, fellows, and junior faculty and served as the senior author on >40 trainee publications. His research on TB diagnostics and case-finding has advanced the field of implementation science, improved clinical and public health outcomes, and informed TB guidelines, policies, and practices endorsed by policymakers in the US and partner countries. He is committed to advancing implementation science by mentoring the next generation of global health investigators to improve the health of Americans in the U.S. and abroad. Mentoring Plan. Dr. Davis is PI of an NHLBI R01-funded, cluster-randomized implementation trial of TB adherence strategies and is Associate Director of a Fogarty D43 research training program. These roles provide a strong platform for recruiting and mentoring junior investigators in patient-oriented implementation research to improve short- and long-term TB treatment outcomes. Over the award period, he will provide structured career development and implementation science mentoring to 20 junior investigators and strengthen durable training pathways at US and partner institutions to build a cadre of researchers prepared to improve population health outcomes, reduce costs, and increase satisfaction. Research Plan. Dr. Davis will expand his research and mentoring program to address TB-related disabilities. He will introduce systematic screening for mental health conditions, respiratory impairment, and exercise intolerance among people with TB (with and without HIV) using validated instruments. He will adapt and pilot peer-facilitated rehabilitation strategies and evaluate their feasibility, acceptability, and appropriateness to inform future trials and implementation. This work will generate rigorous preliminary data and practical strategies to improve post-TB care through mentored research aligned with NIH priorities.

Michigan Department of Health and Human Services

MDHHS funds nonprofits, local health departments, and community organizations providing public health, mental health, substance use treatment, child welfare, and social services to vulnerable Michigan residents.

NIMH - National Institute of Mental Health

Project Summary Schizophrenia (SZ), a major chronic psychiatric illness, is characterized by psychotic symptoms, negative symptoms (e.g., lack of motivation, social withdrawal), cognitive deficits, and impaired social and occupational functioning. Despite advances in understanding the illness, diagnosis still relies on psychiatric interviews and the exclusion of medical or substance-induced psychosis. Likewise, treatment response, typically taking several weeks, is assessed via interviews without reliable biomarkers to guide treatment decisions. This lack of clinically relevant biomarkers represents a significant gap in the field. MicroRNAs (miRNAs), small non-coding RNAs crucial for gene expression regulation, can target hundreds of messenger RNAs and have been implicated in complex diseases like schizophrenia. MiRNA dysregulation in schizophrenia has been demonstrated in genome-wide association studies, human post-mortem brain tissue analyses, and biological fluid studies. Most miRNA studies in biological fluids related to SZ have focused on miRNAs in blood, either as circulating free cell or within peripheral blood mononuclear cells. A new approach being tested in depression and other neurological illnesses involves measuring miRNAs contained in neural-derived extracellular vesicles (NDE) isolated from plasma. NDEs, isolated using brain-specific surface markers, carry an enriched cargo of brain-predominant miRNAs, offering a less invasive window into central nervous system processes. This study will investigate plasma NDE miRNAs as diagnostic and treatment response biomarkers in first-episode schizophrenia (FES) using two approaches. The first approach involves a mechanistic clinical trial with first- episode schizophrenia (FES) participants. This population was specifically chosen to minimize confounding effects associated with prolonged antipsychotic exposure and extended illness duration. Aim 1 will compare plasma NDE miRNA profiles between 80 acutely psychotic FES participants before initiation of controlled treatment and 80 healthy volunteers. Aim 2 will assess baseline and change scores of plasma NDE miRNAs as predictors of response to 12 weeks of controlled treatment with aripiprazole or risperidone. Our second approach will leverage our participation in the Psychiatric Biomarkers Network (PBN), a multi-site consortium focused on fluid biomarkers in psychosis spectrum disorders. We will analyze blood and cerebrospinal fluid (CSF) samples from 60 early-phase schizophrenia participants and 60 healthy volunteers from the PBN to validate our findings in an independent sample and correlate plasma NDE miRNAs with CSF extracellular vesicle miRNAs (Aim 3). This will assess the ability of NDE miRNAs to reflect central nervous system abnormalities as measured in CSF. Successful completion of these aims will provide preliminary evidence for the utility of plasma NDE miRNAs as biomarkers in schizophrenia, paving the way for future refinement, validation, and clinical implementation.

NICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development

PROJECT SUMMARY Concussion and mental health are two significant public health problems disproportionately affecting youth. Con- cussions can severely impact developing brains and are potentially linked to mental health issues like anxiety, depression, and suicidality. Early detection of at-risk youth using artificial intelligence and machine learning (AI/ML) techniques is crucial for timely referrals and treatment. However, current AI/ML models often rely solely on structured electronic health records (EHR) data, neglecting other data types like unstructured clinical notes or wearable sensor data from nonclinical settings. Additionally, many models lack human-centered AI design principles, resulting in rapid abandonment by end-users during deployment. To address these gaps, we have assembled an interdisciplinary team to develop a multimodal AI-based data collection system, MindGuard (Aim 1), use MindGuard to collect multimodal nonclinical data from youth concussion patients aged 11-17 in home settings (Aim 2), develop and evaluate a risk prediction model for post-concussion mental health sequelae using large-scale EHR and MindGuard-collected small-scale nonclinical data (Aim 3), and create and evaluate a hu- man-centered AI system with an explainable risk prediction dashboard to support clinicians decision-making (Aim 4). Our long-term goal is to prevent mental health sequelae and aid concussion recovery in youth. We will use a large EHR dataset of approximately 20,000 youth concussion patients aged 11 to 17 from Nationwide Children’s Hospital (2013-2025). This dataset will be linked to unstructured clinical notes, SDoH, and small-scale multimodal nonclinical data collected prospectively using MindGuard. MindGuard includes data from wearable and smart speaker devices used by 150 youth concussion patients aged 11 to 17. We will use the linked full data to develop and evaluate an AI/ML predictive model for mental health sequelae post-concussion and create an interactive dashboard for clinicians. The main study outcomes will be measured as diagnoses of mental health disorders and self-harm. This project is significant as it addresses two major public health issues affecting youth. It is innovative in its use of wearable sensors, large language model (LLM)-based voice interactions, prospec- tively collected multimodal patient data, advanced AI/ML techniques, and an interactive decision support dash- board. The findings will have a substantial impact by facilitating early detection and timely treatment for at-risk youth to mitigate the risk of mental health sequelae among youth with concussion.

Minnesota Department of Human Services

MN DHS funds nonprofits, tribal nations, and community organizations providing mental health, substance use treatment, disability services, child welfare, economic assistance, and social services to vulnerable Minnesotans.

NIMH - National Institute of Mental Health

Project Summary Psychosocial stress in childhood is a prominent risk factor in the development, severity, and outcomes of internalizing disorders. Stress may impact pediatric mental health by disrupting homeostatic pathways, such as sleep and energy metabolism that can be indexed using mitochondrial biomarkers. Mitochondria, with broad roles in cellular energy and metabolic homeostasis, may contribute to stress-associated physiological wear and tear and serve as a target for intervention in children with internalizing disorders. Mitochondrial DNA (mtDNA) contains unique inflammatory and cell-signaling properties and is actively released as cell-free mtDNA (cf- mtDNA) in response to psychosocial stressors, promoting inflammation and oxidative damage. Levels of cf- mtDNA appear to fluctuate across days and throughout the day and may have a circadian rhythm. Importantly, pervasive disturbances in sleep are observed in both severe stress and mental health disorders and sleep impairment interferes with mitochondrial maintenance. Recent preclinical work indicates that sleep is required for homeostatic oxidative recovery of mitochondria and emerging clinical research demonstrates that circadian disruption is associated with dysregulation of cf-mtDNA. Taken together, this work suggests that stress- induced changes in mitochondrial signaling may contribute to physiological dysfunction and symptoms, potentially due in part to stress effects on sleep. Quantification of cf-mtDNA is now accessible through saliva and may hold promise as a robust biomarker of the dynamic effects of stress and behavior on psychiatric symptoms. The proposed study will recruit N=60 children ages 9-12 with internalizing disorders from a day hospital program. At the time of admission, children and caregivers will each provide baseline assessments of cumulative stress history, sleep disturbances and behavioral health symptoms over the past month, and assessment of a range of internalizing and externalizing symptoms. Following recruitment, children and caregivers will provide daily diary assessments of stress exposure, sleep, and symptoms, and salivary samples assessed for cf-mtDNA across two weeks. This study will 1) characterize baseline cross-sectional associations of levels of cf-mtDNA with cumulative early life stress, baseline sleep disturbances, and baseline internalizing symptom severity and 2) examine daily fluctuations of cf-mtDNA in association with daily stressors (type, severity, and timing), sleep (duration, timing, regularity and quality), and mental health symptoms. By investigating stress-associated mitochondrial processes and sleep in children with psychopathology, this study will yield clinically relevant information, consistent with NIMH Strategic Plan Strategy 2.2, to identify mechanisms of risk to guide the development of novel treatment targets for children with acute psychiatric pathology. Further, data from this study will be used to inform an R01 application investigating cf-mtDNA and additional mitochondrial indices and inflammatory targets in a larger, more definitive study of children with internalizing disorders.

NIMH - National Institute of Mental Health

The training and research plans described in this K23 Career Development Award will enable Dr. Kunmi Sobowale to achieve his long-term career goal of becoming an independently-funded investigator using mobile device technologies to facilitate screening, risk stratification, and personalized prevention and treatment for perinatal and infant mental health. To accomplish this goal, Dr. Sobowale aims to 1) Develop proficiency in the design of longitudinal studies and the statistical methods and skills to process and analyze intensive longitudinal data with a focus on mobile technologies; 2) Develop competence in signal processing and the methods of feature selection, and in particular the application of these methods to speech acoustic analysis; 3) Develop skills in research methods to assess the parent-child interaction and emotion regulation in early childhood. UCLA provides a rich environment for this training plan with a combination of didactic support and hands-on mentorship from leaders in depression neurobehavioral phenotyping, longitudinal study design and analysis, mobile health research, and child socioemotional development as well as the caregiver-child interaction in clinical and non-clinical populations. The training goals will be supported by and applied to the proposed research study. The objective of this longitudinal study of mother-infant dyads is to use mobile sensing devices (audio recorders and Bluetooth sensors) to enable daylong naturalistic assessment of the mother-child interaction. The focus will be mother-infant conversational turns, a key indicator of interaction quality, that are negatively affected by postpartum depression. The study will examine, in turn, how conversational turns affect child emotion regulation and, finally, will explore whether conversational turns are associated with mother-infant co-regulation and relationship quality. Aim 1 of this prospective longitudinal study investigates whether maternal postpartum depressive symptoms at 6 weeks are associated with conversational turn consistency at 3 and 6 months postpartum. Aim 2 examines whether conversational turn consistency at 3 and 6 months is associated with mother-reported child emotion regulation and whether it moderates the effectiveness of infant use of regulation strategies on distress (i.e., emotion regulation) during the still-face paradigm at 6 months postpartum. Aim 3 examines the association between conversational turn consistency at 3 and 6 months with observed mother-child co-regulation (mother-infant affect matches during the still-face paradigm) and mother-reported relationship quality at 6 months. This proposal is aligned with the National Institutes of Mental Health Strategic Objective to develop and assess novel mobile technology and digital health tools to enable objective measurement of behavior and intervention effects on symptom expression and functional outcomes in naturalistic environments. Ultimately, this sensor-based approach will facilitate large-scale assessment of the maternal-child interaction for screening and risk stratification and inform parent-child interventions for mother-infant dyads in the context of maternal postpartum depression.

NIMH - National Institute of Mental Health

ABSTRACT Suicide is a critical public health issue and a leading cause of death in the United States. Individuals living with chronic pain face more than double the suicide risk compared to the general population. Despite this elevated risk, the mechanisms linking chronic pain to suicide remain unclear, and there are no established, targeted suicide prevention strategies for this growing and underserved population. The Catastrophizing, Anxiety, Negative Urgency, and Expectancy (CANUE) model offers an innovative framework for understanding suicide risk in the context of chronic pain. Originally developed to explain substance use vulnerability, CANUE posits that pain promotes maladaptive coping through negative reinforcement, and that cognitive-affective vulnerabilities—such as intolerance of uncertainty (IU) and anxiety sensitivity (AS)—amplify distress and motivate escape-based behaviors like suicide. IU reflects aversion to ambiguity, while AS reflects fear of anxiety- related bodily sensations. Both are theorized to heighten emotional reactivity to pain and fuel the desire for relief, including suicidal thoughts and urges. However, no study has directly tested this model in the context of chronic pain and suicide risk. The goal of this R21 study is to generate novel empirical data to determine how IU and AS interact to shape pain-related distress and momentary suicide risk using an innovative, multimodal research design. We will recruit 90 adults with chronic musculoskeletal pain and elevated suicide risk. Participants will complete a comprehensive laboratory session that includes validated self-report and behavioral tasks assessing IU, AS, and other CANUE-related factors, as well as quantitative sensory testing (QST) to assess pain sensitivity and affective responses to pain in a controlled setting. Immediately following the lab session, participants will complete a 21-day ecological momentary assessment (EMA) protocol, delivering a mix of time-based, random, and event-based mobile surveys to assess fluctuations in pain, pain-related affect, suicidal ideation, and escape- motivated thoughts in real time and natural environments. This combination of experimental and real-world methods will allow for the first rigorous test of whether IU and AS have unique and interactive effects on pain sensitivity, pain-related affect, and recent suicidal ideation in the lab (Aim 1), and whether they moderate the dynamic, moment-to-moment associations between pain, affect, and suicide risk in daily life (Aim 2). We hypothesize that participants with higher levels of IU and AS will report greater recent suicidal ideation severity and show greater pain-related negative affect in response to experimental pain. We also anticipate that IU and AS will moderate real-time links between pain and suicidal ideation in the natural environment. By leveraging laboratory and ecological data, this project represents a significant and innovative step forward in understanding the mechanisms underlying suicide risk in chronic pain. Findings will advance theoretical models of suicide and pave the way for more personalized, mechanistically informed prevention strategies for this high-risk and understudied population.

NIGMS - National Institute of General Medical Sciences

PROJECT SUMMARY There is a mental health crisis among graduate students, encompassing both mental illness and broader well-being issues. These challenges don’t disappear when graduate students enter the classroom, research lab, or their mentor’s office. The pressures of academia can exacerbate these issues. As a result, faculty mentors frequently interact with students experiencing psychological distress, either acutely in the moment or more chronically over time. However, faculty mentors are ill-equipped to navigate these mental health challenges. Most faculty mentors did not receive training about mental health or effective interventions during their graduate education. Furthermore, empirically supported faculty mentorship training focused on mental health among graduate students is virtually nonexistent. Thus, faculty mentors are left to navigate complex dynamics with their students without the necessary training to do so effectively. To address this gap, we propose a series of self-paced modules for mentors of graduate students: a foundational module on interpersonal responsiveness plus 6 additional modules in the mental health toolkit. These 6 toolkit modules will cover cognitive reframing, self-affirmation, mindful self-compassion, dialectical thinking, community building, and mental health crisis support. These modules are firmly grounded in existing research in psychology and relationship science about interpersonal interactions, mental health and well-being, and coping strategies. Our team is highly interdisciplinary, with expertise in psychology, relationship science, education, mentorship, experimental design, and assessment and evaluation. In addition, there are 3 advisory boards (content expertise advisory board, interdisciplinary faculty advisory board, interdisciplinary graduate student advisory board) of 5 members each, with members representing various disciplines, institutions, and geographic areas across the U.S. Thus, the modules will be grounded in the empirical literature, utilize the expertise of the PI and Co-Is, and also be guided by input from faculty mentors and graduate students across disciplines, institutions, and geographic areas in the U.S. First, we will develop the modules using a multi-step, iterative process. Next, we will pilot the modules and further refine the module materials. Then, we will conduct a randomized controlled trial (RCT) assessing the efficacy of the modules, disseminate the results, and disseminate the modules. Evidence-based training for mentors navigating mental health challenges among their graduate students is lacking. Thus, these modules will fill an important gap in higher education training and in the scientific literature on mentorship.

NIMH - National Institute of Mental Health

Contact PD/PI: lewis, elinor PROJECT SUMMARY Second generation antipsychotics (SGAs) are widely used clinical tools for the treatment of severe mental illness. However, their utility is highly variable, and they take weeks to become effective. The mechanisms behind this time course are not understood. SGAs are thought of as antagonists at the D2 dopamine receptor. Yet our recent work suggests that some SGAs function as arrestin-biased agonists at the less-characterized D3 dopamine receptor (D3R). Activation of the arrestin-3 pathway leads to degradation of D3R, potentially altering response to these drugs over time. I have generated preliminary data that shows mice grow tolerant to preclinical measures of SGA activity after chronic treatment of an arrestin-biased SGA. I hypothesize that D3R neurons are the locus of tolerance to select SGAs, and this tolerance is driven by decreased D3R membrane expression caused by arrestin-3 recruitment to D3R. I will use in vivo optical methods to assess changes in D3-neuron activity after chronic SGA treatment. I will also measure behavioral tolerance to SGA treatment in transgenic mice with altered abilities to degrade D3Rs and compare D3R levels using saturation binding and PET scans. This project will reveal mechanisms of tolerance to select SGAs at gross anatomy, cell- type, and protein levels. Project Summary/Abstract Page 6

NCCIH - National Center for Complementary and Integrative Health

Project Summary/Abstract Research: Fear activates the fight or flight stress-response, leading to rapid changes in behavior and physiological accommodations via the sympathetic nervous system. While the stress response facilitates survival from an acute threat, inappropriate activation or delayed termination after threats have passed can be maladaptive. Indeed, inappropriate sympathetic activation is a hallmark of psychiatric diseases such as post- traumatic stress disorder and major depressive disorder. Conversely, non-invasive brain modulation techniques such as transcranial direct current stimulation, which induces diverse physical and mental health benefits, may function in large part through its ability to mitigate the stress response. Together, this suggests that the neural circuits regulating the sympathetic nervous system could be an important therapeutic target. To map the central circuits regulating the adrenal gland, an essential effector of the fight-or-flight sympathetic response and the principal source of circulating epinephrine, I will use monosynaptic rabies. My preliminary data show that the adrenal medulla receives innervation not only from well-established hypothalamic nuclei, but also, surprisingly, from the motor cortex. The proposed project will expand upon this finding: In Aim 1) I will rigorously map the connections between the motor cortex and the adrenal gland and in Aim 2) I will investigate how these cortical neurons modulate epinephrine release and the physiological and behavioral response to stress. These aims will expand our understanding of this newly discovered neural circuit and its role underlying important mind-body interactions. Career development: This five-year research career development program will advance the career of a promising physician-scientist studying the neural circuits underlying mind-body connections as they relate to the physiological effects of stress. This proposal builds upon the candidate’s extensive background in molecular neuroscience and behavioral genetics, by promoting Dr. Greene’s acquisition of several necessary technical skills and extensive training to ensure that the candidate develops superb professional skills. The training goals are reflected in the expertise of the mentors (Dr. Andrés Bendesky and Dr. Rui Costa), tailored seminars and didactics, and the strong neuroscience training environment at Zuckerman Mind Brain and Behavior Institute. By completing the proposed studies and training plan, the candidate will acquire a unique and highly valued skill set that will support a successful transition to becoming an independent investigator.

NIMH - National Institute of Mental Health

PROJECT SUMMARY Top-down signals from the prefrontal cortex have long been postulated to regulate hippocampal function as part of numerous cognitive and emotional processes, but the specific pathways mediating top-down control have been unclear. We have found a novel long-range GABAergic pathway from prefrontal cortex to hippocampus that represents a potential substrate for top-down control. Notably, this pathway seems to operate in an unusual manner: by inhibiting disinhibitory circuits. Our initial studies found that these prefrontal- hippocampal GABAergic projections can promote object exploration by enhancing hippocampal representations of object locations and associated network oscillations. However, two major questions remain unresolved. First, prefrontal GABAergic neurons which project to the hippocampus are heterogeneous and the significance of this is unknown. Second, the detailed circuit mechanisms through which long-range GABAergic projections from prefrontal cortex alter hippocampal information processing remain unclear. The goal of this project is to first and foremost, elucidate mechanisms through which long-range prefrontal-hippocampal projections shape computation in downstream circuits, and second, relate these to the heterogeneity of long- range GABAergic neurons. This project will specifically test our hypothesis that long-range GABAergic projections exert top-down control over the hippocampus by targeting disinhibitory microcircuits, thereby regulating how competing input regions recruit and entrain feedforward inhibition in the hippocampus. This could explain how hippocampal circuits switch between different information processing modes, each characterized by rhythmic synchronization with a different upstream region. Furthermore, we may identify different subtypes of long-range GABAergic neurons that each promote synchrony with a unique input region, elucidating organizational principles and functional implications for the heterogeneity of long-range GABAergic neurons.

NIMH - National Institute of Mental Health

PROJECT SUMMARY Working memory allows past events to be transiently maintained in the brain so that it can be compared with ongoing experiences to drive behavior. This cognitive process has been shown to be severely impacted by the progression of many neuropsychiatric diseases and disorders. Thus, it is critical to understand the components of working memory to determine how normal mental function can be restored. Working memory must be selective to relevant stimuli and resistant to noise or irrelevant stimuli. It has been proposed that information is maintained through persistent activity at the single-cell or population level, either among local recurrently connected neurons or through long-range loops across multiple brain areas. Alternatively, it has been proposed that information could be maintained through activity-silent intracellular processes which are defined by specific genes and molecules. These theories are not necessarily mutually exclusive and may both be implemented in the nervous system. To achieve a comprehensive understanding of these mechanisms, it is necessary to investigate working memory across multiple biological scales spanning genes, cell types, local circuit dynamics, brain-wide communication, and behavior. Using a combination of multi-area two-photon calcium imaging, long-range anatomical tracing, cell-resolution optogenetic manipulation, and comprehensive spatial transcriptomic analysis, we will dissect working memory circuits as animals perform sensory-guided working memory tasks. In Aim 1, we will determine how specific stimuli are maintained in working memory by monitoring and perturbing local and long-range cortical activity to distinguish working memory maintenance from sensory-to-working-memory transformations. In Aim 2, we will determine the cellular and molecular mechanisms supporting local working memory by combining functional connectivity and gene expression measurements to distinguish their contributions to persistent activity and activity silent properties. Through this, we will determine the precise local and long-range dynamics that underlie working memory and the cellular and molecular properties that support these computations.

National Institutes of Health

-Purpose. The purpose of this Funding Opportunity Announcement (FOA) issued by the National Institute on Drug Abuse and the National Institute of Mental Health, National Institutes of Health, is to solicit Research Project Grant (R01) applications from institutions/organizations that propose to identify chromosomal loci and/or genetic variation in genes and haplotypes that are associated with either increased or decreased vulnerability to, dependence on, and/or treatment response for addiction to stimulants (e.g., cocaine, amphetamine, caffeine), narcotics (e.g. opiates), nicotine, benzodiazepines, barbiturates, cannabis, hallucinogens, and/or multiple drugs of abuse and/or their associated mental co-morbidities (e.g., major depression, schizophrenia, bipolar disorder) in human beings or animal models. Similarly, there is interest in chromosomal loci and/or genetic variation in genes and haplotypes that are associated with differences in responses to treatment for addiction to drugs of abuse, and treatments for co-morbid disorders -Mechanism of Support. This FOA will utilize the NIH Research Project Grant R01 award mechanism. -Funds Available and Anticipated Number of Awards. Awards issued under this FOA are contingent upon the availability of funds and the submission of a sufficient number of meritorious applications.

NIMH - National Institute of Mental Health

Project Summary/Abstract Dopamine neurons in the ventral tegmental area (VTA) fire action potentials in complex patterns of tonic and phasic activity in response to environmental stimuli and during behavioral tasks. Transcriptomic, anatomical, and functional studies have established that VTA dopamine neurons can be divided into multiple subpopulations with variable gene expression, projection patterns, and response profiles. We recently completed a transcriptomic study that identified genetic markers for three distinct subpopulations of VTA dopamine neurons, and also found evidence for variability in ion channel gene expression between populations that correlated with differences in activity-dependent gene expression. However, much remains unknown regarding how specific genes encoding ion channels, receptors, transcription factors, or other signaling components contribute to the variability in baseline physiological properties observed across the VTA. Here we propose to combine slice electrophysiology recordings of VTA dopamine neurons with post-hoc single-cell sequencing analysis (i.e. patch-seq), which will allow us to directly correlate gene expression and physiological properties in order to identify candidate genes that may be key drivers of the variability between subpopulations. We also propose to validate and utilize a novel dual-recombinase CRISPR/Cas9 system for targeted gene mutagenesis in intersectional neuronal populations, which will provide a mechanism for testing gene function with unprecedented precision. We will use this approach to test the function of two candidate ion channel genes, the potassium channels Kcnh5 and Kcnh7, previously identified in our transcriptomic study as potential contributors to dopamine neuron action potential firing properties. We hypothesize that these genes are important for enabling rapid action potential firing in highly excitable dopamine neurons found in specific subpopulations. As a whole, with this proposal we aim to generate a valuable dataset linking gene expression in VTA dopamine neurons with physiology and subpopulation identification, as well as develop an intersectional gene mutagenesis strategy that can be used throughout the brain to precisely target neuronal subpopulations to test gene function. With this approach, we hope to facilitate future precision targeting of the dopamine system and dopamine-dependent behaviors.

NIMH - National Institute of Mental Health

Abstract/Summary Advances in antiretroviral therapy (ART) have reduced the incidence of severe clinical neurocognitive complications associated with chronic HIV infection, such as HIV-associated dementia (HAD). Nevertheless, nearly half of people with HIV (PWH) still experience asymptomatic neurocognitive disorder (ANI) and mild neurocognitive disorder (MND). Opportunities for using novel, data-driven approaches, such as Artificial Intelligence (AI) in making predictions, real-time monitoring, or improving clinical decision-making to address HIV-related neurocognitive disorders (HAND) proliferate but have yet been fully realized. Recent studies have employed machine learning (ML) and/or deep learning (DL) techniques to either cluster neurocognitive phenotypes or identify key predictors of neurocognitive impairment in PWH. Data from these studies, however, are typically “siloed” and unimodal (e.g., only electronic health records [EHR] data or imaging data). Given the broad spectrum of modalities of neurocognitive disorder, multimodal approach (i.e., integration of different data modalities) provides opportunities to increase robustness and accuracy of diagnostic and prognostic models by utilizing complementary and supplementary information in modalities. However, such multimodal approach is limited often due to the lack of multimodal data and advanced methodologies such as multimodal AI. One novel and ambitious initiative funded by the NIH to advance precision medicine is the All of Us (AoU) Research Program, a centralized data repository, offering secure access to de-identified multimodal data (e.g., EHR data, genomic data, survey data, and imaging data) from almost one million program participants. In our preliminary study, we have developed a computational phenotyping that identified 6,664 confirmed PWH among 633,000+ participants as of October 2023. In response to RFA-MH- 26-105, we propose to apply multimodal AI with a series of longitudinal EHR data (laboratory and medication), genomic data, self-reported survey data (e.g., lifestyle, physical measurement, healthcare access), and imaging data in AoU to 1) identify different biotypes of neurocognitive disorders in PWH (e.g., ANI, MND, HAND) and employ ML/DL approaches to cluster neurocognitive phenotypes; 2) develop, evaluate, and validate multimodal AI models to predict neurocognitive disorders in PWH accounting for comprehensive information and enhance the model interpretability through synergistic integration of a domain-specific knowledge graph; and 3) develop a multimodal AI based decision-making prototype to assist with the identification of PWH with risk of neurocognitive disorders and pilot test its feasibility, usability, and implementation strategies in clinical settings. Personalized risk prediction through multimodal AI could improve the predictive accuracy and early detection of neurocognitive decline in PWH and inform tailored intervention and treatment for PWH. The insights gleaned from our project could also be a demonstration of the power of cutting-edge multimodal AI models to expand our capacity to accelerate HIV care and address the dynamic, complex, and evolving HIV epidemic.

NICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development

Project Summary Sustained attention (SA)—the ability to maintain engagement with people or objects over time—is a foundational skill that supports early learning across domains, including language, cognitive development, and social interaction. Disruptions in early SA have been linked to later difficulties in academic achievement, emotion regulation, and mental health. Yet, little is known about how SA naturally emerges, stabilizes, and becomes self-directed in infancy, particularly in everyday social contexts. This project investigates how SA develops through dynamic coordination among behavioral, neural, and autonomic systems, captured in real time during naturalistic parent–infant interactions. We will conduct a longitudinal study of typically developing infants between 6 and 30 months, integrating head-mounted eye tracking (ET), electroencephalography (EEG), and heart rate monitoring (ECG). This multimodal design enables precise identification of SA episodes and their physiological signatures as they unfold in the real world. We hypothesize that caregiver scaffolding—such as holding—shapes the salience and structure of infants’ attention, triggering coordinated multisystem engagement that supports the emergence of self-directed SA. We will characterize age-related changes in SA, examine its variation across social contexts, and assess whether early multisystem patterns predict later individual differences in attention control, language development, and neural function. This project is innovative in its longitudinal, ecologically grounded approach to studying attention, combining first-person ET with neural and autonomic measures during live interaction. Findings will advance theories of developmental attention and clarify how early multisystem dynamics contribute to variation in cognitive and social outcomes.

NIMH - National Institute of Mental Health

Psychotic disorders are a leading contributor to the global disease burden, causing high levels of disability and increased mortality. To improve outcomes, it is essential to identify and treat patients in the early stages of psychotic disorders, especially before overt symptoms appear. Yet, despite decades of research, we are unable to accurately identify early on individuals who will progress to develop a psychotic disorder, even those who are clinically high risk for psychosis, due in part to small sample sizes and extant approaches that do not capture the multifactorial etiology of psychotic disorders. There is therefore an urgent need to substantially improve prognostic precision. Critically, accurate and robust prognostic markers are needed to understand the origins and progression of psychosis and to identify precise neurobiological targets for early treatment. Newly available large-scale multimodal data—clinical, cognitive, and neurobiological—as well as exciting recent advances in artificial intelligence models and methods that overcome limitations of extant approaches offer an unprecedented opportunity for developing accurate and robust prognostic markers for psychosis. The overarching goal of our proposal is to identify accurate and robust multimodal prognostic markers for psychosis using a novel data-driven AI-based computational framework. Building on our highly encouraging preliminary results, we will use an innovative approach combining our recent work on AI models and explainable AI methods as well as integrative theoretical models of psychosis with a wealth of newly available large-scale multimodal data from multiple consortia. The specific objectives of our proposed work are threefold. In Aim 1, we will identify prognostic markers using clinical, cognitive, and neurobiological data to predict future psychosis transition, particularly in youths at clinical high risk. In Aim 2, we will evaluate the generalizability and the temporal (longitudinal) stability of the identified prognostic markers. In Aim 3, we will determine whether the identified prognostic markers predictive of future psychosis transition in youths at clinical high risk are a characteristic trait of psychosis. Through the successful completion of the work described here, our multidisciplinary team is uniquely positioned to transform our understanding of the mechanisms associated with the risk for and development of psychotic disorders, as well as identify neurobiological targets. Ultimately, these advances will lead to the development of individualized prognostic tools and early targeted treatments for psychosis and, more broadly, advance precision psychiatry.

NIMH - National Institute of Mental Health

ABSTRACT Studying multi-animal interactions is crucial for understanding cognitive mechanisms underlying social behaviors and decision-making processes. Observing collective behaviors can reveal the neural basis of social bonding, aggression, and cooperation. However, current methods for automating multi-animal behavior analysis are often too simplistic and may neglect interactions, context, and the complexity of multi-animal behavior. Here we argue that understanding complex animal behaviors requires breaking them down into fundamental units, and then forming an understanding of how these units combine to form more complex natural behaviors. Our approach is inspired by linguistic concepts, where basic elements (syllables) combine according to gram- matical rules (syntax) to convey meaning (intent). We aim to dissect multi-animal behaviors by identifying these fundamental units and their combinations to gain deeper insights into social interactions. To achieve our goals, we will organize the effort along three main aims, progressing from behavioral syllables (Aim 1), to syntax (Aim 2), and finally to intent (Aim 3). In Aim 1, we will develop methods for learning latent representations from multi-animal behavioral time se- ries and segment them into behavioral syllables—brief movements or actions efficiently describing behavioral features. The syllables from multi-animal data are mainly social syllables representing exchanges between indi- viduals that best capture or generate natural behaviors. In Aim 2, we will extract motifs, i.e., longer sequences of interactions, to comprehend complex social behaviors. To solve such a long sequence learning problem, we propose transformers for their ability to capture long-term and intricate patterns in sequential data. We will craft a compositional model that combines behavior syllables to form motifs, effectively revealing behavior syntax. In Aim 3, we will develop a novel framework for understanding intent and rewards in multi-animal behaviors, extending inverse reinforcement learning to include multiple animals. Each animal will be treated as a decision- maker whose state space will be expanded to include others' states and actions. We aim to reveal underlying intents driving social behaviors. The project will produce innovative tools for modeling multi-animal behavior, transforming raw data into frame-level behavioral syllables and constructing abstract representations of behavioral rules, patterns, and in- tent. We will provide accessible software and demos for the research community. The project's impact will be substantial, offering advanced computational tools to deepen insights into the cognitive mechanisms of social in- teractions, cooperative behaviors, and decision-making processes. This framework will enhance the analysis and prediction of complex social behaviors across species, benefit the fields of behavioral and social neuroscience, and contribute to long-term advancements in human health research.

National Alliance on Mental Illness

Supports community mental health programs, education, and advocacy.

National Alliance on Mental Illness

Grants for mental health programs specifically designed for veterans and military families experiencing mental illness.

Substance Abuse and Mental Health Services Adminis

National Child Traumatic Stress Initiative - Community Treatment and Service Centers (CTS)

Substance Abuse and Mental Health Services Adminis

The purpose of the NCTSI-III program is to create and operate Community Treatment and Service Centers to increase and deliver access to effective childhood trauma treatment services for children, youth, and their families, who experience traumatic events.