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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 A major challenge in clinical genomics is the interpretation of variants of uncertain significance (VUS), which comprise the majority of disease-associated mutations cataloged in human genetic databases. This limitation is especially acute in neuropsychiatric and neurodevelopmental disorders, where cellular context and gene function are tightly intertwined. CACNA1C, which encodes the L-type calcium channel Cav1.2, exemplifies this challenge: common variants are strongly associated with psychiatric disorders such as schizophrenia and bipolar disorder, while rare mutations cause severe developmental syndromes like Timothy Syndrome. To address the need for scalable, physiologically relevant functional annotation, we propose to develop a next-generation neural multiplexed assay of variant effect (MAVE) platform that combines prime editing with a calcium-activity–based phenotyping system in human neurons. Using ~2,000 CACNA1C variants as a test case, we will integrate precision genome editing with a novel biochemical calcium recorder (CaST) in hiPSC-derived neurons to assess variant impact on calcium signaling. This approach enables classification of variants into gain-, loss-, or benign- function categories in a scalable and context-specific manner. By overcoming limitations of existing MAVEs in fidelity, scalability, and neuronal relevance, this platform will accelerate variant interpretation, enable therapeutic prioritization, and be broadly extensible to other calcium channel genes and functional modalities.

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

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

National Institutes of Health

Reissue of PAR-20-118. This Notice of Funding Opportunity (NOFO) encourages applications to advance the discovery, preclinical development, and proof of concept (PoC) testing of new, rationally based candidate agents and neurostimulation approaches to treat mental disorders, substance use disorders (SUDs) or alcohol use disorder (AUD), and to develop novel ligands and circuit-engagement devices as tools to further characterize existing or to validate new drug/device targets. Partnerships between academia and industry are strongly encouraged. This NOFO using the U01 mechanism supports a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies Projects seeking support for a research program of multiple projects directed toward a specific major objective, basic theme or program goal, requiring a broadly based, multidisciplinary and often long-term approach should consider the companion U19 FOA.

National Institutes of Health

Reissue of PAR-20-118. This Notice of Funding Opportunity (NOFO) encourages applications to advance the discovery, preclinical development, and proof of concept (PoC) testing of new, rationally based candidate agents and neurostimulation approaches to treat mental disorders, substance use disorders (SUDs) or alcohol use disorder (AUD), and to develop novel ligands and circuit-engagement devices as tools to further characterize existing or to validate new drug/device targets. Partnerships between academia and industry are strongly encouraged. This NOFO using the U01 mechanism supports a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies Projects seeking support for a research program of multiple projects directed toward a specific major objective, basic theme or program goal, requiring a broadly based, multidisciplinary and often long-term approach should consider the companion U19 FOA.

National Institutes of Health

Reissue of PAR-20-119. This FOA encourages applications to advance the discovery, preclinical development, and proof of concept (PoC) testing of new, rationally based candidate agents and neurostimulation approaches to treat mental disorders, substance use disorders (SUDs) or alcohol use disorder (AUD), and to develop novel ligands and circuit-engagement devices as tools to further characterize existing or to validate new drug/device targets. Partnerships between academia and industry are strongly encouraged. This FOA supports a research program of multiple projects directed toward a specific major objective, basic theme or program goal, requiring a broadly based, multidisciplinary and often long-term approach. Projects seeking support for a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies should consider the companion U01 FOA.

National Institutes of Health

Reissue of PAR-20-119. This FOA encourages applications to advance the discovery, preclinical development, and proof of concept (PoC) testing of new, rationally based candidate agents and neurostimulation approaches to treat mental disorders, substance use disorders (SUDs) or alcohol use disorder (AUD), and to develop novel ligands and circuit-engagement devices as tools to further characterize existing or to validate new drug/device targets. Partnerships between academia and industry are strongly encouraged. This FOA supports a research program of multiple projects directed toward a specific major objective, basic theme or program goal, requiring a broadly based, multidisciplinary and often long-term approach. Projects seeking support for a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies should consider the companion U01 FOA.

Administration for Children and Families - OFVPS

The Resource Centers support efforts to prevent and respond to family, domestic, and dating violence by providing information, training, and technical assistance to individuals, organizations, government agencies, and communities.The National Resource Centers on Domestic Violence focus on strengthening services and knowledge in the field. One center provides training and technical assistance on domestic violence programs, research, and services for victims and their children. Another maintains a national resource library to collect, analyze, and share information on domestic violence, prevention strategies, and services for adult and youth victims.The National Indian Resource Center works with tribes and tribal organizations to improve responses to domestic violence and increase safety for Indian women. It also coordinates with federal partners that serve Native communities.Special Issue Resource Centers address key systems that impact victims of domestic violence. These centers provide training and technical assistance on responses within the justice system, child protective services, health care, and mental health systems. Additional centers focus on improving services and prevention efforts for racial and ethnic minority communities.Native-focused resource centers, including those serving Native Hawaiian and Alaska Native communities, build capacity among tribes, organizations, and service providers. They coordinate with the National Indian Resource Center and deliver culturally relevant prevention and education efforts.The National Resource Center to Expand Services for Children, Youth, and Abused Parents strengthens support for non-abusing parents and their children, including efforts to prevent or reduce foster care involvement.Sexual Assault Technical Assistance Centers support grantees in improving sexual assault prevention and response through specialized expertise and training.

NIMH - National Institute of Mental Health

PROJECT SUMMARY P HIV Pre-Exposure Prophylaxis (PrEP)harmacist autonomous-prescribing of is an HIV prevention strategy that is rapidly rising in the US – the number of states with pharmacist-prescribed PrEP has over quintupled in the past five years andPrEP prescribing by pharmacists increased doubled within four years of the first state policy. Yet, studies of this HIV prevention strategy have been concentrated in a few cities and the impact of these policies have not been evaluated. Thus, we lack rigorous national data about when, where or to whom pharmacists are prescribing PrEP, whether it is happening in areas where PrEP is most needed, or the public health impact it might be having on PrEP adherence, persistence, or subsequent HIV rates. This study’s primary purpose is to evaluate, on a national level, where pharmacist-prescribed HIV PrEP is happening or not happening within states that allow it, who it reaches, and what population-level impacts it is having on HIV. Our team was the first to identify a novel population-based surveillance metric of PrEP adherence using national pharmacy claims data, finding that nearly 1 in 5 patients with an insurance-approved, new, oral PrEP script who did not pick up PrEP from their pharmacy, of which, over 70% still did not pick up PrEP within 365 days, conferring up to 5 times higher HIV risk than those who picked up PrEP consistently. We then assessed non-adherence for by the specialty of prescribing provider, but we could not assess pharmacists as a group of providers, as legislation for pharmacist-prescribed PrEP was too new for that earlier 2019 data capture. We now embark on a timely investigation of pharmacist-prescribed PrEP, to better understand where it is happening or not happening, what populations are best reached by pharmacists, and HIV rates of patients prescribed PrEP by pharmacists compared with other prescribers. We use a nationally representative claims dataset (IQVIA) that captures ~85% of all PrEP prescriptions in the US, including public, private and individual payers, along with patient demographics and National Provider Identifier, linked to prescriber data from the National Plan and Provider Enumeration System to: compare trends and timing of pharmacist-prescribed PrEP to other prescribers, mapping to where PrEP need is high (i.e., high HIV incidence) but allowed pharmacist- prescribing is not happening (Aim 1); identify the profile of patients most reached by pharmacist-prescribed PrEP (Aim 2); and compare PrEP adherence, persistence, and HIV incidence at one year, among those prescribed by pharmacists versus other prescribers (Aim 3) as an indicator of whether patients remain engaged in PrEP care after initiation at pharmacies. Our team includes expertise in epidemiology, pharmacy, biostatistics, GIS, and HIV prevention. The study has policy implications for how pharmacists are engaged in care, and where care needs to be expanded based on populations being underserved, with the expected outcome of fully integrating pharmacists into HIV prevention.

National Institutes of Health

The purpose of this NOFO is to build research about the effectiveness, implementation, and optimization of family navigation ED diversion models for non-urgent mental health problems. Models of interest are designed to (a) utilize triage tools to identify mental health acuity, (b) facilitate engagement in mental health services and needed resources, and (c) provide support, knowledge about the mental health condition, and facilitate linkages/address barriers to help-seeking among families.

National Institutes of Health

The purpose of this NOFO is to build research about the effectiveness, implementation, and optimization of family navigation ED diversion models for non-urgent mental health problems. Models of interest are designed to (a) utilize triage tools to identify mental health acuity, (b) facilitate engagement in mental health services and needed resources, and (c) provide support, knowledge about the mental health condition, and facilitate linkages/address barriers to help-seeking among families.

National Institutes of Health

The purpose of this NOFO is to build research about the effectiveness, implementation, and optimization of family navigation ED diversion models for non-urgent mental health problems. Models of interest are designed to (a) utilize triage tools to identify mental health acuity, (b) facilitate engagement in mental health services and needed resources, and (c) provide support, knowledge about the mental health condition, and facilitate linkages/address barriers to help-seeking among families.

National Institutes of Health

The purpose of this NOFO is to build research about the effectiveness, implementation, and optimization of family navigation ED diversion models for non-urgent mental health problems. Models of interest are designed to (a) utilize triage tools to identify mental health acuity, (b) facilitate engagement in mental health services and needed resources, and (c) provide support, knowledge about the mental health condition, and facilitate linkages/address barriers to help-seeking among families.

NC Department of Health and Human Services

NCDHHS funds nonprofits, health organizations, and community agencies providing mental health, substance abuse, developmental disability, public health, and social services to vulnerable North Carolinians.

NIEHS - National Institute of Environmental Health Sciences

PROJECT SUMMARY/ABSTRACT Chronic kidney disease (CKD) and hypertension (HTN) are substantial public health concerns in the US and are important risk factors for other adverse outcomes including acute kidney injury and premature mortality. CKD and HTN are typically diagnosed later in life, yet our understanding of the prenatal and early life environ- mental determinants of reduced kidney function and HTN across childhood and early adulthood remains incipi- ent. This research, however, faces several barriers including lack of assessment of both neighborhood- and individual-level environmental stressors at specific early life stages coupled with long-term follow-up from birth to early adulthood. This project will address these research gaps by leveraging high-quality data from Project Viva, an ongoing longitudinal prospective pre-birth cohort of mother-child pairs followed since pregnancy. The overall goals of the proposed project are to examine the extent to which early-life exposure to disadvantaged neighborhood contexts and nephrotoxicants (i.e., air pollutants and metals) leads to later life kidney dysfunc- tion and higher blood pressure (BP). The investigators will: (Aim 1) examine associations of early-life neighbor- hood environment with kidney function and BP across childhood and early adulthood; (Aim 2) assess associa- tions of individual-level early-life exposure to candidate nephrotoxicants with kidney function and BP from mid- childhood to early adulthood; and (Aim 3) characterize urinary proteomic signatures underlying altered kidney function and BP trajectory from childhood to early adulthood, and examine these signatures as potential mark- ers of toxicant exposure. This innovative proposal will be the first to examine both neighborhood- and individ- ual-level environmental determinants of kidney function and BP trajectories. We will identify actionable risk fac- tors and molecular signatures to identify high-risk individuals and pinpoint when primordial prevention efforts have the greatest potential to prevent future CKD and HTN.

NIA - National Institute on Aging

PROJECT SUMMARY Cancer, mental health disorders, and substance use are leading causes of disease burden, disability, and premature death in the United States, with particularly large impacts among low-income populations. Identifying effective strategies to increase cancer screening and preventive care visits among low-income populations is critical to reducing this burden. Identifying effective strategies to increase cancer screening and preventive care visits among low-income populations is critical to reducing this burden. Because poverty is spatially concentrated in the U.S., income gains accruing to some residents of low-income neighborhoods could shift broader neighborhood economic conditions and generate health “spillover effects” among nonrecipients — through peer diffusion of healthy behaviors and other neighborhood improvements such as parks, transportation, and health clinics resulting from increased local economic activity. Evidence of neighborhood spillover effects on health could deepen understanding of how neighborhood economic conditions drive population health, equipping health systems and public health practitioners with evidence to better anticipate disease burden, prioritize community health investments, and improve health outcomes in low-income communities. We propose the first study to rigorously investigate neighborhood spillover effects of increased neighborhood income on health outcomes. We will study changes in neighborhood income resulting from neighborhood-level earned income tax credit (EITC) distributions, leveraging exogenous changes in distributions over time to rigorously estimate spillover effects. We will analyze individual level electronic health record data from 8.2 million patients in 1,222 primary care practices in all 50 states in the U.S. that is linked to U.S. Census Bureau data and tax returns. This unique dataset includes a large sample of individuals who live with or in proximity to each other, providing sufficient statistical power to estimate neighborhood spillover effects. We will investigate spillover effects stratifying by age to understand effects across the life course. Our Specific Aims are to: 1) estimate spillover effects of neighborhood economic conditions on health; and 2) test the robustness and heterogeneity of neighborhood spillover effects. Health outcomes from 2010-present will be characterized using electronic health records data and include cancer screening, preventive visits, mental health, and substance use disorders. We will estimate effects of state EITC distribution changes using staggered difference-in-differences with an event study framework. We will evaluate the reliability of our spillover effect estimates through multiple robustness checks and assess spillover effect heterogeneity by individual, neighborhood, and EITC characteristics. Our novel approach will serve as a template for future studies that investigate how health interventions targeting neighborhood economic conditions influence health.

NIMH - National Institute of Mental Health

Summary This proposal seeks to develop a networked trial emulation framework to enhance real-world evidence (RWE) generation on the causal effects of glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) on mental health outcomes. While GLP-1 RAs have shown benefits for type 2 diabetes and obesity, their potential impact on neuropsychiatric health remains underexplored due to methodological challenges, including measurement errors, immortal time bias, incomplete drug adherence data, and decentralized multi-institutional data sources. This project addresses three critical gaps: (1) the need for systematic-error-corrected target trial emulation framework to improve causal effect estimation for mental health outcomes; (2) the lack of scalable methods for multi-institutional causal inference in neuropsychiatric research; (3) the challenge of accurately phenotyping drug adherence and mental health conditions using structured and unstructured clinical data. The proposed framework integrates systematic-error correction techniques, federated learning, natural language processing (NLP)-enhanced phenotyping, and tensor train decomposition to overcome these limitations. The success of this project will establish a robust, scalable approach for high-quality RWE generation, advancing the understanding of GLP-1 RAs' potential neuropsychiatric effects and informing clinical and regulatory decisions.

NIDA - National Institute on Drug Abuse

Chronic cannabis use is linked to poor physical and mental health. Young adults (age 18-21) with anhedonia, defined as deficient processing and experiencing of pleasure and rewards, are especially at risk for escalating their cannabis use. Anhedonia is a key transdiagnostic feature of many disabling conditions that have high rates of cannabis use and cannabis use disorder. Examining mechanisms of cannabis use escalation in young adults with elevated anhedonia is therefore highly significant as it would inform targeted prevention efforts for individuals who are at elevated risk. One reason young adults with anhedonia may be at risk for chronic cannabis use is because they abnormally process delta-9-tetrahydrocannabinol (D9-THC), the psychoactive ingredient in cannabis linked to the rewarding and reinforcing properties of cannabis. The few studies on the acute effects of D9-THC on reward processing have yielded mixed results, potentially due to not taking individual differences in anhedonia into account. Indeed, our preliminary study suggests that an individual’s level of anhedonia impacts how acute administration of D9-THC (relative to placebo) affects one’s neural response to rewards. Given that sensitivity to acute effects of other drugs (e.g., stimulants, alcohol) is a known risk factor for chronic use of those drugs, D9- THC’s effect on reward processing may be a mechanism for escalation to chronic cannabis use among young adults with anhedonia. The first goal of this project is therefore to examine how an acute laboratory administration of D9-THC (vs. placebo) impacts two aspects of reward processing: how individuals (a) anticipate receiving rewards (reward anticipation) and (b) learn associations between their actions and rewarding outcomes (reward-based reinforcement learning [RBRL]). Deficits in reward anticipation and RBRL have been robustly linked with anhedonia, but only examined in a handful of small D9-THC administration studies. The second goal of this study is to test if sensitivity to D9-THC’s effects on reward processes serves as a biomarker for escalation to chronic cannabis use in young adults with anhedonia. We will recruit 144 young adult (aged 18-21) occasional to regular cannabis users (who use less than daily) with a clinically significant range of anhedonia. At baseline, participants will undergo two double-blind, within-subject, drug-challenge visits (placebo vs. D9-THC), during which they will complete the reward anticipation and RBRL tasks in a fMRI scanner. All participants will then be followed for 2 years to assess future cannabis use and cannabis use disorder symptoms. A unique feature of this novel study is the assessment of two types of reward responses to acute D9-THC, as well as a longitudinal follow-up among a clinically-relevant sample. In sum, the present proposal has the potential to identify novel biomarkers for escalation to chronic cannabis use in an understudied, clinically relevant population – work that will ultimately inform targeted intervention and prevention efforts among young adult cannabis users at risk for chronic use.

NIA - National Institute on Aging

ABSTRACT Menopause is a major neuroendocrine transition experienced by nearly two million individuals in the United States each year. It is associated with increased rates of depression, social withdrawal, and loss of sexual motivation, posing significant challenges to mental health, interpersonal relationships, and public health. While hormonal decline has been implicated, the neural circuit mechanisms underlying these behavioral symptoms remain poorly understood. This proposal seeks to define how hormonal decline during reproductive aging disrupts a specific hormone-sensitive neural circuit and impairs female sexual behavior. Our work focuses on a projection from Cckar-expressing neurons in the ventromedial hypothalamus (VMHvlCckar) to the anteroventral periventricular nucleus (AVPV), a pathway that is essential for female sexual behavior and highly sensitive to ovarian hormones. Using a physiologically relevant menopause model induced by 4-vinylcyclohexene diepoxide (VCD), which gradually depletes ovarian follicles without surgery, we will determine how hormonal decline alters both the structural connectivity and functional activity of this projection. Specific Aim 1 will test whether structural atrophy of the VMHvlCckar to AVPV projection occurs with hormonal decline and whether it is reversible by hormone supplementation. Specific Aim 2 will examine how hormonal decline affects activity along this circuit, revealing where circuit dysfunction arises. Specific Aim 3 will use optogenetics to test whether activating this pathway restores sexual behavior and whether AVPV activity is necessary for hormone-induced behavioral rescue. By linking hormone-sensitive circuit remodeling to behavioral impairments, this study will identify new neurobiological targets for intervention. The findings may guide the development of circuit-based therapies to support mental health and social functioning during aging.

NIMH - National Institute of Mental Health

Project Summary Biological accounts of reinforcement learning posit that dopamine encodes reward prediction errors (RPEs), which are multiplied by a learning rate to update state or action values. The learning rate is often assumed to be constant, but studies in humans, monkeys, rats, and mice, have found behavioral evidence for dynamic learning rates. In volatile environments, dynamic learning rates allow animals to learn faster when the world is changing, and more slowly when the world is stable. While dopamine is thought to instantiate RPEs, we recently found that dopamine release in the ventral striatum did not reflect learning rates, suggesting that dopamine-independent mechanisms determine the rate of error-driven learning. Moreover, we present strong preliminary data showing that inactivation of the orbitofrontal cortex (OFC) eliminates dynamic learning rates behaviorally, and that OFC neurons that project to the ventral striatum seem to encode the learning rate in their firing rates. In this proposal, we will determine how OFC projections to the ventral striatum dictate the rate of error-driven learning at behavioral and neural levels. This proposal will use a novel behavioral paradigm in rats, in which reward statistics vary over latent blocks of trials. We previously found strong behavioral signatures of dynamic learning rates in rats performing this task. High-throughput behavioral training will generate dozens of trained subjects for experiments in parallel, accelerating the rate of research progress. We will use optogenetics and electrophysiology to record from and manipulate OFC neurons that project to the ventral striatum, to determine if this projection pathway dictates behavioral learning rates (Aim 1). We will use electrophysiology and optogenetics to relate behavioral learning rates and activation of OFC neurons that project to the ventral striatum to trial-by-trial changes in evoked spiking in the striatum (Aim 2). We will use optical methods to measure dopamine release in the striatum and activation of OFC axon terminals, while simultaneously recording action potentials from the ventral striatum, to relate endogenous fluctuations in coincident dopamine and OFC inputs to trial-by-trial plasticity of evoked spiking (Aim 3). These experiments will test key predictions of “three-factor” plasticity rules in behaving animals. These experiments will address a major open question, which is how specific output pathways from OFC interact with downstream circuits to coordinate value-based decisions and learning. Neuromodulatory systems including dopamine are implicated in myriad neuropsychiatric disorders including schizophrenia and depression. A greater understanding of the circuit mechanisms by which they coordinate different aspects of behavior and interact holds promise for revealing novel therapeutic targets for these disorders.

NIMH - National Institute of Mental Health

PROJECT SUMMARY/ABSTRACT Early life stress (ELS) significantly increases the risk of postpartum psychiatric conditions, especially cognitive impairment. Given the time gap between ELS events and the postpartum period, identifying high-risk individuals with ELS and intervening early appears feasible. However, understanding this longitudinal relationship through human studies alone is challenging, necessitating animal models. Most animal studies on postpartum psychiatric disorders focus on behavioral changes after hormone injections, neglecting the pathological trajectory from ELS to postpartum cognitive impairment. To address this, we developed a new mouse model to explore how ELS affects postpartum behaviors. In our model, female mice exposed to mild social isolation during late adolescence (SILA) do not show increased levels of plasma corticosterone (CORT) or significant behavioral changes. Pregnancy/delivery alone do not lead to notable abnormalities. Notably, by postpartum day (PD) 7, mice exposed to SILA exhibit behavioral changes related to mood, social cognition, and parenting only when combined with pregnancy and delivery. SILA dams also exhibit elevated and sustained plasma corticosterone (CORT) levels, mirroring those in postpartum depression patients. While CORT levels in SILA and non-SILA dams are similar in late pregnancy, SILA dams show higher levels from PD 0, persisting for at least three weeks postpartum, aligning with long-lasting behavioral changes. Blocking glucocorticoid receptors (GR) during the first postpartum week improves SILA dams’ behavior, highlighting CORT’s role in ELS-associated postpartum changes. Our proposal will use this new mouse model to functionally and transcriptionally investigate how enhanced and sustained levels of plasma CORT alter neuronal function and lead to behavioral deficits in the first postpartum week, focusing on social novelty recognition. Our preliminary data suggest that removing GR expression or optogenetically activating the glutamatergic neuronal projections from the anterior insula to the prelimbic cortex (AIPrL glutamatergic pathway) can ameliorate deficits in social novelty recognition observed in SILA dams. CORT influences gene transcription via GR, a nuclear receptor acting as a transcriptional activator and suppressor. Thus, we hypothesize that continuous GR activation by CORT during the initial postpartum week disrupts the transcriptional regulation in the AIPrL glutamatergic pathway, reduces their synaptic activities in PrL, and consequently impairs social novelty recognition in stressed dams. This study will determine how CORT affects the AI-PrL glutamatergic pathway via GR in stressed dams, elucidate the molecular mechanisms involved, and evaluate the impact on social novelty recognition and other behaviors. The findings aim to explain how adolescent psychosocial stress leads to social cognition deficits in mothers, guide interventions to mitigate these effects, and provide crucial insights into postpartum social behavior impairments affecting mothers, their children, and families.