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NIMH - National Institute of Mental Health

Project Summary Adolescent social media use has risen dramatically. This rise has occurred alongside with increasing rates of depression, anxiety, and other psychopathological symptoms. However, current research lacks the understand- ing of which specific online experiences drive mental health risks. This project pioneers the use of AI-based screenomic analysis to transform over 38 million smartphone screenshots from 154 adolescents into structured records of digital experiences, enabling the first scalable, causal study of risky online exposures and their bidirec- tional links to psychopathological symptoms. Towards this objective, we propose the following specific aims: (1) we will develop computational pipelines to detect event-level risky exposures—individual encounters with harm- ful content (e.g., violence, suicide, body image) or risky social interactions (e.g., cyberbullying, peer pressure). Vision-language models (VLMs), fine-tuned and personalized using few-shot adaptation, will integrate visual and textual cues to classify these exposures. These event-level data will be linked to biweekly measures of anxiety and depressive symptoms using Random-Intercept Cross-Lagged Panel Models to assess reciprocal causality. (2) We will move beyond single events to model sequential risky digital exposures—chains of online behaviors that may amplify risk (e.g., influencer viewing → body image discussion → late-night browsing). Multi-image VLMs and sequential pattern mining will identify common trajectories, and Marginal Structural Models will test whether these digital patterns predict symptom escalation, or vice versa. By advancing from broad “screen time” metrics to fine-grained digital biomarkers, this research will establish a mechanistic understanding of how online experiences shape mental health in adolescence. The resulting computational tools and insights will lay the foun- dation for precision monitoring and prevention strategies, informing policy, clinical interventions, and youth digital well-being initiatives.

NIMH - National Institute of Mental Health

Depression is a major public health issue affecting hundreds of millions globally, with significant implications for suicide risk and overall health. Reliable assessment of depression severity is crucial for the development and validation of new medications, yet the current FDA-approved scales, the Hamilton (HAM-D) and Montgomery and Åsberg (MADRS) Depression Rating Scales, are limited by their subjective nature and lack of standardization. These limitations introduce measurement error and contribute to the particularly high failure rate of Phase 3 clinical trials in depression. The Depression AICOA®, a novel multimodal AI-based tool, has been developed to address these challenges by providing a more reliable and standardized method for assessing depression severity. Utilizing a computational approach that objectively measures multimodal features of depression severity, AICOA® has shown high concurrent reliability with HAM-D scores. Recognizing its potential, the FDA has recently accepted AICOA® into its Innovative Science and Technology Approaches for New Drugs (ISTAND) Pilot Program, marking it as the first AI and Digital Health Technology, as well as the inaugural Neuroscience project in the program. This SBIR project aims to advance AICOA® to regulatory qualification and a commercially ready stage through extensive clinical validation. The project will support the technical development and clinical validation of AICOA® through a comprehensive study. The outcomes of this research will enable AICOA® to progress with FDA qualification as a Drug Development Tool, paving the way for more precise and reliable depression assessments in clinical trials, ultimately leading to the development of more effective treatments.

NIMH - National Institute of Mental Health

The AI-Facilitated Partner Communication for PrEP study aims to enhance HIV prevention among women by empowering them with skills to discuss pre-exposure prophylaxis (PrEP) with male sexual partners. Existing PrEP interventions rarely address the complex barriers to partner communication that influence PrEP uptake. This R34 proposal aims to develop and pilot a Virtual Practice Environment (VPE) using large language models (LLMs) to simulate realistic conversations that allow women to practice PrEP communication strategies in a supportive, risk-free setting. This study offers an innovative, scalable approach to strengthening PrEP implementation efforts by addressing partner-level barriers.

National Institutes of Health

The National Institute of Mental Health (NIMH) seeks research applications to support the NIMH HIV/AIDS Research Centers (ARC) program, including Developmental Centers (D-ARCs) and full AIDS Research Centers (ARCs). These Research Centers aim to capitalize on the coordinated infrastructure to advance high-impact, interdisciplinary HIV/AIDS research. The ARC program supports innovative research across basic, neuro-HIV, behavioral and social, clinical, translational, implementation science, and data science domains. Centers are expected to foster scientific collaboration, accelerate innovation, and strengthen dissemination of research advances to implementing agencies, affected communities, and other stakeholders. Applications should align with the National HIV/AIDS Strategy, the NIH Office of AIDS Research (OAR) Strategic Plan, and the NIMH Strategic Plan for HIV research. Applications are not being solicited at this time. This notice is being issued to provide potential applicants with ample time to develop strong, collaborative, and responsive project plans. Research teams that have expertise in establishing and sustaining collaborations with academic institutions, community partners, government agencies, industry, and other scientific networks to enhance the impact of Center-supported activities are encouraged to apply to this NOFO.

National Institutes of Health

<p>The National Institute of Mental Health (NIMH) seeks research applications to support the NIMH HIV/AIDS Research Centers (ARC) program, including Developmental Centers (D-ARCs) and full AIDS Research Centers (ARCs). These Research Centers aim to capitalize on the coordinated infrastructure to advance high-impact, interdisciplinary HIV/AIDS research. The ARC program supports innovative research across basic, neuro-HIV, behavioral and social, clinical, translational, implementation science, and data science domains. Centers are expected to foster scientific collaboration, accelerate innovation, and strengthen dissemination of research advances to implementing agencies, affected communities, and other stakeholders.</p><p>&nbsp;Applications should align with the National HIV/AIDS Strategy, the NIH Office of AIDS Research (OAR) Strategic Plan, and the NIMH Strategic Plan for HIV research. Applications are not being solicited at this time. This notice is being issued to provide potential applicants with ample time to develop strong, collaborative, and responsive project plans. Research teams that have expertise in establishing and sustaining collaborations with academic institutions, community partners, government agencies, industry, and other scientific networks to enhance the impact of Center-supported activities are encouraged to apply to this NOFO.</p><p>&nbsp;</p>

NIMH - National Institute of Mental Health

Project Summary/Abstract Ecological Momentary Assessment (EMA) studies capture unprecedented data about suicidal thoughts and be- haviors (STBs) via smartphones and wearable biosensors. While promising, EMA studies are expensive to run, require a large staff, and are limited in scientific value due to three data analysis challenges. These challenges create a bottleneck for suicide research. Challenge 1: small data size. Even the largest of EMA studies yield modest sample sizes with low compliance. This bars applications of (data-hungry) deep learning (DL) methods, successful in other areas of healthcare. Challenge 2: stochasticity. STBs are, in part, driven by stochastic (or random) external events that cannot be captured (e.g. reactions to triggering stimuli). Methods that do not model external stochasticity often learn spurious correlations, making incorrect and overconfident forecasts of future pa- tient outcomes. Challenge 3: empirically testing theories of suicide. Empirically evaluating theories with data is difficult given their verbal (non-quantitative) nature; mathematically formalized theories require an extreme level of specification detail, making it difficult for clinical and machine learning (ML) researchers alike to determine which details capture the high-level idea of the theory. As such, current methods struggle to accurately forecast STBs, identify those at imminent risk, and test psychological theories of suicide. Our central hypothesis is that encod- ing clinical knowledge in DL models addresses key data analysis challenges. We define qualitative clinical knowledge (QCK) as clinical knowledge that is difficult to mathematize, like intuition. Encoding QCK in DL meth- ods will provide the model additional supervision, reducing its over-reliance on limited data (Challenge 1). Guided by clinical knowledge, it will discover scientifically viable associations between EMA outcomes and unobserved external factors, avoiding spurious correlations due to stochasticity (Challenge 2). Lastly, our method will pro- vide clinicians with a mechanism for encoding their knowledge into the model without specifying uninterpretable mathematical details (Challenge 3). Our project has three aims. Aim 1: develop a new DL model, tailored for noisy, irregularly-sampled, partially-observed EMA data. Aim 2: identify types of QCK that clinicians can reliably provide, encode them into our DL model, and assess their predictive value. Exploratory Aim 3: prototype an interactive modeling paradigm that algorithmically solicits clinicians for QCK (from Aim 2) into the DL model (from Aim 1). Expected Outcomes: This project will yield (1) theoretically and empirically validated ML methods for use in future scientific and clinical work, (2) new insights/findings from existing EMA data, increasing the scientific yield from previous NIH-funded projects, (3) an interactive ML paradigm for embedding clinical knowledge in DL methods, useful in all mental health and healthcare contexts, and (4) highly optimized, modular open-source code, available for the broader community to apply and adapt to their needs.

NIMH - National Institute of Mental Health

Abstract Neurodevelopmental and neurological and mood disorders manifest a high prevalence in modern society and a marked sex bias, but their etiology remain poorly understood, hampering our efforts for their prevention, diagnosis and treatment. Although genome-wide association studies in the last two decades have greatly advanced our knowledge of the genetic basis for these conditions, identified candidate genes and their genetic variations only explain a small percentage of clinical cases. This divergence is dramatically illustrated by autism and schizophrenia, whose heritability is close to 80%, but for which genetic factors account for less than 20% of clinical cases. To identify new contributors to the etiology of these and related neurodevelopmental conditions, we propose that alterations in thyroid hormone states during development, which may occur due to environmentally-driven epigenetic phenomena, maternal thyroid disease or exposure to endocrine disruptors, contribute to the generation of neurodevelopmental disease and fit two well-established but undefined components in their etiology: environmental influence via epigenetic alterations and sex bias. We hypothesize that changes in the allelic expression and gene dosage of the imprinted gene Dio3, which controls thyroid hormone action in the developing central nervous system, leads to neurological deficits, affecting gene expression programs in the developing brain, brain sexual differentiation, brain morphology and behavior of relevance to neurodevelopmental and psychiatric conditions. We will use transgenic mouse models with alteration in Dio3 and developmental thyroid hormone exposure to test these hypotheses in the following Specific Aims: (i) To determine the neurological impact of aberrant Dio3 allelic expression; (ii) To evaluate the role of full DIO3 deficiency and altered Dio3 allelic expression in brain sexual differentiation and associated disease-relevant behaviors with a sexual bias. By using a dynamic mouse model of epigenetic dysregulation of Dio3, we anticipate our project will demonstrate that modifications in brain thyroid hormone states during development exert a substantial effect on the gene expression programs of the central nervous system, ultimately leading to disease-relevant neurological deficits impacting corticogenesis, brain morphology and hydrocephalus, and behaviors related to depression, anxiety, sociability, hyperactivity, sexual activity and reward. We ultimately expect that epigenetic markers and dysregulation of the Dio3 gene, and the changes in thyroid hormone status associated with them, can be used as evidence of exposures to thyroid hormone earlier in life and be utilized as predictors of susceptibility to neurodevelopmental conditions.

NIMH - National Institute of Mental Health

PROJECT SUMMARY Despite the broad use of antibody tools, their reliability and scalability remain major challenges for reproducible cellular and anatomical profiling in large tissue volumes, such as whole-mouse and human brains. In this project, we propose to develop an AI-assisted platform for recombinant antibody resources that meets the high standards required to advance brain research. By integrating our teams' complementary expertise in AI algorithms, structural analysis, antibody validation, and brain imaging, we aim to create a synergistic technical and resource platform for curating recombinant antibody tools, establishing a new paradigm for antibody applications in brain research. As part of the BICCN/BICAN effort, we have validated an extensive collection of commercial and open- source monoclonal antibodies using a high-content screening pipeline, providing a strong experimental foundation for recombinant antibody curation. However, the current experimental approach has limitations in efficiently selecting and prioritizing thousands of monoclonal antibody sequences for cost-effective conversion and validation. It also relies solely on existing sequences without effective optimization or design using structural information for diverse applications. Our integrated approach, leveraging our expertise in AI-based protein structure prediction, modeling, and simulation, will analyze antibody sequences to provide a comprehensive understanding of recombinant antibody structural properties, including antigen binding sites and affinities across target species. This will significantly accelerate the conversion and validation of recombinant antibodies. Additionally, we will continue refining our approach to enhance flexibility in optimizing and designing recombinant antibodies, tailoring them to specific epitopes and cross-species targets for diverse applications. We will also develop a curated database of recombinant antibody resource for easy reference and adaptation within the field. This database will include a comprehensive collection of validated recombinant antibodies, featuring their defined sequences, predicted antibody-antigen binding structures, 2D IHC data in mouse and human, and 3D whole mouse brain labeling datasets for key BICCN targets. To ensure broad accessibility, the database will be available through a user-friendly online portal. This integrated recombinant antibody platform, rAb-GenAI, will be open to incorporating advanced AI algorithms and continuously refined through iterative experimental feedback. Both our AI pipeline and recombinant antibody resource will be highly scalable and adaptable, maximizing cost efficiency to support consistent large-scale profiling, including human brain cohort mapping. Through this project, we aim to establish a new paradigm for antibody-based research, laying the foundation for brain-wide proteomic investigations across species and enabling studies on whole brain cellular and structural dynamics in health and disease.

American Psychological Foundation

Supports psychological research, education, and programs addressing mental health, behavioral health, and social issues.

NIMH - National Institute of Mental Health

The anterior cingulate cortex (ACC) is a heterogenous structure that is strongly connected with the amygdala. Its subdivisions are critical for unique limbic and cognitive functions. The subgenual ACC (sgACC, Brodmann area 25/14c), implicated in major depression in humans, is a key node of the salience network and is important for arousal state modulation and valuation of sensory information. In contrast, the perigenual ACC (pgACC, Brodmann area 32/24b) is dorsal to the sgACC, and is important for cognitive functions including decision-making and conflict monitoring. Despite known functional differences in sgACC and pgACC, the main cortical and thalamic drivers of the ACC subregions are not fully understood in higher species. My preliminary data using paired injections in the same hemisphere indicates that sgACC afferent networks involve midline thalamic nuclei, insula, and medial wall inputs. In contrast, pgACC receives unique inputs from mediodorsal (MD) thalamus, orbital, and lateral PFC inputs (9/46) that carry information important for spatial and temporal localization of salient stimuli. These data indicate specific functional hubs in sgACC and pgACC. Despite evidence for discrete afferent networks to the sgACC and pgACC, the amygdala projects broadly to both. sgACC and pgACC inputs to the amygdala converge onto glutamatergic ‘hot spots’ in the basal and accessory basal nuclei, which in turn project back to the sgACC and pgACC. New molecular evidence indicates diverse glutamatergic neuronal phenotypes in the basal and accessory basal nucleus. We hypothesis a unique subtype comprises both the sgACC and pgACC projection. Recent preliminary evidence suggests that despite an apparently broad projection to the sgACC and pgACC, specialized glutamatergic neurons in specific amygdala subregions may be important in regulating these two regions. Aim 1 analyzes paired retrograde tracer injections in sgACC and pgACC in the same animal, and uses standard correlation and also unsupervised cluster analysis to identify cortical and thalamic afferent ensembles across the sgACC-pgACC trajectory. Aim 2A will define transcriptome shifts in neuron populations along the basal and accessory basal amygdala, beginning broadly and then focusing on glutamatergic neuron signatures using single-nucleus RNA sequencing. Spatially defined localizations of specific glutamatergic subtypes will be validated with in situ hybridization (RNAScope). Aim 2B will determine the molecular features of amygdala- sgACC and amygdala-pgACC projection neurons, following injections in Aim 1. These results will then be integrated with the results of cortical-thalamic input networks for comprehensive analysis of sgACC and pgACC connectivity. This research is part of a comprehensive training plan with direct mentorship in experimental design, techniques, field knowledge, scientific writing and career development, supported by my Sponsors, my Collaborator, and their respective institutions (URMC, Emory, and Wake Forest).

NIMH - National Institute of Mental Health

Project Summary There is clear evidence that early intervention benefits autistic children’s short- and long-term development. However, the rising autism prevalence is overwhelming the public health system’s capacity. As a result, many autistic children cannot access timely diagnostic and intervention services. Self-directed telehealth interventions (i.e., online programs that parents can complete via computer, tablet, or mobile device, without provider coaching or feedback) offer parents a way to gain evidence-based strategies that they can implement with their children without having to navigate barriers such as long intervention waitlists and high cost. However, parent engagement with the program, and child outcomes, in existing self-directed interventions vary widely, and little is known about which families can benefit from low- vs. high-support interventions. The proposed sequential multiple assignment randomized trial (SMART) will evaluate an adaptive, parent- mediated, telehealth intervention that teaches basic principles of autism intervention with varied levels and types of support. 340 parent-child dyads will be initially randomized to either a self-directed intervention (OPT- In-Early) or OPT-In-Early with automated support. Parent engagement with OPT-In-Early and comprehension of intervention content will be monitored over a 1-month period. At that point, parents with “low engagement” (i.e., parents who either did not use the intervention or did not demonstrate learning of key concepts) will be re- randomized to either individual or group clinical support, with a goal of increasing engagement with the intervention and ultimately improving child outcomes. Multi-method, longitudinal assessments will be used to rigorously evaluate implementation and outcomes. Child outcomes will include assessment of key developmental domains that are impacted by autism. This research is significant because it will be the first time a self-directed telehealth intervention for autism is optimized for greatest engagement. This proposal is aligned with NIMH’s Strategic Plan Goal 4.2, to improve mental health by expediting adoption and implementation of an evidence-based intervention. This study will generate the evidence necessary to implement an adaptive intervention at-scale, thereby increasing the capacity of the existing public health system to offer tailored and cost-effective interventions to young autistic children and their families.

NIMH - National Institute of Mental Health

PROJECT SUMMARY Major depressive disorder (MDD) is a leading cause of disability, with substantial individual and societal costs. The heterogeneity of MDD and the lack of predictive tools for individualized treatment present significant challenges to effective care. This proposal aims to leverage recent advances in foundation models, a type of artificial intelligence (AI) that has demonstrated remarkable success in natural language processing, to develop a neuroimaging-based tool that can aid in prognostication, treatment stratification, and biotype discovery in MDD. Foundation models are pretrained on massive datasets, enabling them to learn generalizable features that can then be adapted to smaller, more specific datasets. This approach is ideally suited for psychiatric neuroimaging, where clinical datasets are scarce; however, non-clinical datasets like the Human Connectome Project and UK Biobank are extensive. I have developed a functional prototype by adapting a transformer architecture to analyze functional magnetic resonance imaging (fMRI) time-series data and training it on the UK Biobank. Preliminary data generated using this prototype indicate strong potential for this approach. Applying this innovative technique to psychiatry holds great promise for advancing the understanding and treatment of MDD. To achieve this, I propose three specific aims. Aim 1: Use pooled fMRI data from individuals with MDD to fine-tune the pretrained model to decode depression severity and uncover MDD biotypes; Aim 2: Use pooled fMRI scans from longitudinal treatment data to fine-tune the pretrained model to predict antidepressant response and identify neural circuits of treatment response; Aim 3: Prospectively evaluate the performance of MRI-based treatment prediction models in a pilot clinical trial. If successful, this work will yield a novel neurocomputational framework for personalized treatment stratification and significantly advance our understanding of MDD neurobiology and heterogeneity. Through this research, training, and expert mentorship, I will gain expertise in: 1) AI foundation models, including transformer architectures and interpretability techniques; 2) applying foundation models to neuroimaging to generate clinically actionable predictions and mechanistic insights; 3) clinical trial design and analysis of longitudinal data; and 4) professional skills for transitioning to independence. The training plan—which includes coursework, workshops, close mentorship, and hands-on research experience—builds on my existing expertise in neuroimaging, network neuroscience, and clinical psychiatry. Stanford University offers an exceptional environment with access to cutting-edge computational resources, neuroimaging facilities, and a vibrant community of AI experts and clinician-scientists. In sum, through the K23 award, the proposed research, training, mentorship, and pilot data will enable me to successfully compete for independent research funding and establish a high-impact patient-oriented research program in neurocomputational psychiatry at the intersection of AI, neuroimaging, and precision treatment.

NIMH - National Institute of Mental Health

PROJECT SUMMARY/ABSTRACT The K23 application proposes to examine learning and neurocognitive mechanisms underlying food approach in avoidant/restrictive food intake disorder (ARFID) using computational methods and will position the applicant, Marita Cooper, Ph.D., to transition to research independence with expertise using computational modeling to examine mechanisms of restrictive eating disorders (ED) in youth. ARFID is the most prevalent ED in childhood, with sequelae including malnutrition, delayed growth, cardiac complications, and death. Early data suggest youth with ARFID exhibit executive functioning deficits, including weak central coherence and poor response inhibition. These data underly the hypothesis that youth with ARFID may be slow to learn food approach, impacting food intake, and requiring more exposure to novel foods for learning to occur. Knowledge of neurocognition and learning in ARFID is in its infancy, yet computational modeling offers an innovative approach to probe underlying processes and identify target mechanisms related to aberrant food approach. Two approaches with utility in other EDs, active inference and reinforcement learning, have not been applied to ARFID. The study will examine learning mechanisms and neurocognition of aberrant food approach in ARFID. We will recruit 99 youth (66 with ARFID, 33 controls) ages 8-18, matched on age and sex. Participants will complete a three-armed bandit task, assessing learning mechanisms (via food and neutral stimuli), and a meal-based buffet task assessing food approach (macronutrient and caloric intake). We will assess neurocognition, ED symptoms, and approach/ avoidance. Aim 1 hypothesizes that youth with ARFID will exhibit poorer performance (under both neutral and food conditions) than healthy controls and that worse performance will relate to overall intake during the buffet task. Aim 2 follows participants naturalistically, repeating assessments at 6- and 12-month follow-up. We will examine whether baseline performance predicts improvement in ARFID symptoms at follow-up. Aim 3 will compare whether active inference or reinforcement learning models best fit participant learning behavior. The project will be an important major step in developing a data-driven model of ARFID, providing critical information about potential drivers of aberrant food approach. The proposed project will support expert mentorship and training for Dr. Cooper including 1) learning and neurocognitive development in youth; 2) conducting and managing longitudinal research in clinical samples; and 3) practical skills in computational modeling transferrable to future research. The resources of Children’s Hospital of Philadelphia and University of Pennsylvania and an expert team of mentors (with expertise in mechanisms of ARFID/restrictive ED, development, clinical research, and computational modeling) provide an outstanding context to launch Dr. Cooper’s career. Project findings are consistent with the NIMH strategic goal to identify validated targets for intervention and will inform a competitive R01 application examining computational learning mechanisms in a transdiagnostic sample of youth with restrictive ED.

NIMH - National Institute of Mental Health

PROJECT SUMMARY The overarching goal of my program of research is to understand how positive aspects of the parent-child relationship can be leveraged to increase child resiliency in the context of early life adversity, considering the impact of both mothers and fathers. The focus of this K01 award is to characterize father-infant co-regulation at the neural and behavioral level and test its impact on the development of early emotional problems among children exposed to maternal depression in the first year postpartum (postpartum depression; PPD). Infants depend on their caregivers to learn foundational emotional self-regulation skills. Through co-regulation, infants and their caregivers coordinate behavioral, affective, physiological signals that over time support the infant’s ability to self-regulate. Maternal PPD has been found to disrupt mother-infant co-regulation and is associated with significantly increased risk for the development of emotional problems in the child. However, very little research has examined how father-infant co-regulation may influence the risk of emotional problems following exposure to maternal PPD. Recent advancements in neuroimaging technology, specifically the use of near infrared spectroscopy (NIRS) during in vivo naturalistic parent-child interactions, have made it possible to examine neural mechanisms that underlie the development of early emotional self-regulation via parent-infant co-regulation. The Aims of this K01 are to 1) examine how father-infant neural and behavioral co-regulation associate with one another and with fathers’ depression symptoms and coparenting relationship quality, 2) examine maternal PPD as a predictor of father-infant neural and behavioral co- regulation, and sources of heterogeneity and 3) examine the prospective association of father-infant neural and behavioral co-regulation on early emotional problems among infants exposed to maternal PPD. All mothers in the sample (n = 100) will have elevated symptoms of PPD (i.e., EPDS > 10), and must be cohabitating with the infant’s father. Father-infant neural and behavioral co-regulation will be measured during an in-home face-to-face interaction (i.e., play and recovery from a stressor) when infants are 9 months old. The interaction will be assessed using NIRS and videorecorded for later behavioral coding. Child emotional problems will be assessed at 18 months via parental and close caregiver report using clinically validated measures and via in-home observational assessment. To achieve the proposed goals and transition to independence, Dr. Taraban will receive mentored training in 1) developmental affective neuroscience, 2) engaging fathers in research and measurement of the father-infant relationship, and 3) statistical analysis of dyadic neural and moment-to- moment affective data. Dr. Taraban will be supported by a strong team of mentors (Drs. Morgan, Lunkenheimer, Schoppe- Sullivan, and Silk) and consultants (Drs. Goodman, Huppert, and Iyengar) with expertise that spans domains of developmental affective neuroscience, co-regulation, fathering, NIRS, maternal PPD, and time-series analysis. The proposed K01 research aligns with Goals 1 and 2 of NIMH’s strategic plan (Objectives 1.1, 2.1 and 2.2) and is a vital step toward Dr. Taraban’s long-term goal of tailoring parenting-focused interventions to reduce the risk of emotional problems among children exposed to early life adversity.

NIMH - National Institute of Mental Health

Modified Project Summary/Abstract Section HIV pre-exposure prophylaxis (PrEP) is underutilized among women. Identification and evaluation of implementation strategies to support PrEP uptake are crucial to overcoming barriers to PrEP use among women. The proposed study aims to develop and evaluate implementation strategies to increase PrEP uptake among women who could benefit in a high-incidence jurisdiction through integration of PrEP into postpartum care and support the career development of Dr. Caroline Mullis. Despite the many competing priorities of postpartum women (i.e., breastfeeding, sleep deprivation, postpartum depression, etc.), utilization of postpartum care to provide PrEP education and services has the potential to reach many women who: 1) are known to be HIV negative and engaging in condomless sex; 2) may not otherwise be receiving routine healthcare; and 3) are in an age group where most new HIV infections occur. We will develop and evaluate implementation strategies acting at the patient-, provider- and health systems-level to support uptake of PrEP, an evidence-based intervention. We hypothesize that: 1) provider training to support PrEP discussions and prescribing; 2) delivery of routine PrEP education by nurses; and 3) community health worker navigation assistance will target patient-, provider- and systems-level determinants and increase PrEP uptake among women in the Bronx who may benefit. Specifically, in Aim 1, we will evaluate a provider-level implementation strategy to support obstetricians and gynecologists (OBGYNs) prescribing of PrEP in postpartum care, i.e., the GOALS Approach to Sexual Health and History. In Aim 2, using human-centered design methods, we will develop a toolkit for postpartum nurses and community health workers to efficiently deliver information about PrEP. In Aim 3, we will evaluate acceptability, feasibility and preliminary effectiveness of nursing and community health worker delivered PrEP education as a part of routine postpartum care. Training on the GOALS Approach to Sexual Health and History will be delivered to OBGYNs at an institutional Grand Rounds. A survey will assess acceptability and feasibility of the training. Human-centered design methods will be used to engage postpartum nurses, community health workers and postpartum patients in an iterative co-design process to develop a toolkit for use by postpartum nurses and community health workers to deliver education on PrEP. The toolkit will be evaluated in a randomized, controlled pilot trial to evaluate acceptability, feasibility and preliminary effectiveness of nursing delivered PrEP education and a community health worker navigation call at 5 weeks postpartum. Dr. Mullis’ transition to independence as a physician scientist will be directly supported by training and mentorship to acquire additional skills in understanding systems-level determinants to intervention adoption, implementation, human centered design methods, quasi-experimental and other clinical trial designs. Results will inform development of an R01 application designed to assess the scalability and sustainability of these implementation strategies in a multi-site cluster randomized hybrid type 3 trial.

NIMH - National Institute of Mental Health

Project Summary/Abstract Interval timing, the ability to estimate event durations on the scale of seconds to minutes, is crucial for adaptive behaviors. Prior work investigating the neural basis of interval timing has focused on brain circuits in the basal ganglia and frontal and parietal cortices. However, recent research, including our own, indicates that the entorhinal cortex (EC) also plays a key role in the learning of timing behavior. In our recent work, we have discovered "time cells" in the medial entorhinal cortex (MEC) that fire at fixed intervals, forming sequences crucial for timing behavior. In contrast, lateral entorhinal cortex (LEC) neurons exhibit ramping activity over seconds to minutes as animals forage and/or perform spatial navigation tasks. This suggests distinct neural dynamics in the LEC and MEC for encoding elapsed time, hinting at different roles in timing behavior. A major limitation of this interpretation is that all LEC recordings to date have been from animals not engaged in active timing tasks, making it impossible to determine whether these neural correlates of ramping activity are actually involved in timing behavior or are simply a result of other task demands. To determine the functional roles of LEC and MEC in timing behavior, it is necessary to use tasks with explicit timing demands. Using a novel behavioral paradigm in which mice are trained to report non-matching stimuli durations, combined with neural recording and manipulation techniques, this proposal tests a model in which LEC and MEC function together to encode elapsed time and drive interval timing behavior. Specifically, we hypothesize that LEC encodes event boundaries through brief phasic activity, which then helps align sequential dynamics in MEC to these salient moments. In Aim 1, we will determine if LEC activity is necessary to align MEC time cell sequences and whether LEC activity is essential for learning timing behavior. In Aim 2, we will examine neural dynamics simultaneously in LEC and MEC during timing behavior to see if they function independently or in an integrated manner. Since interval timing is a fundamental component of nearly all major brain functions, understanding the cellular and circuit mechanisms of interval timing will provide a basis for understanding how the brain performs complex functions that depend on encoding time on the scale of seconds to minutes. This work also has the potential to guide the development of therapies targeting specific neural mechanisms in a wide range of diseases and psychiatric disorders that display altered temporal processing, including Alzheimer’s Disease, Parkinson’s Disease, and Schizophrenia.

National Institutes of Health

-Purpose. This Funding Opportunity Announcement (FOA) is a program announcement (PA) issued by the National Institute of Neurological Disorders and Stroke (NINDS), the National Eye Institute (NEI), the National Institute on Aging (NIA), the National Cancer Institute (NCI), and the National Institute of Mental Health (NIMH), National Institutes of Health (NIH). The aim of this FOA is to invite applications to study angiogenesis in the nervous system. Specific areas of research this FOA seeks to encourage include study of the mechanisms controlling angiogenic responses to physiological and pathological stimuli, the development and patterning of nervous system vasculature, and the etiology of disorders affecting development and/or ongoing angiogenesis in nervous system vasculature. -Mechanism of Support. This FOA will use the NIH Exploratory/Developmental (R21) grant mechanism and runs in parallel with a FOA of identical scientific scope, PA-08-015, that encourages applications under the NIH Research Project Grant (R01) award mechanism. Please note that NIMH is not participating in the companion R01 FOA. -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.

Health and Human Services Department

ACF/OHS announces its intent to award multiple single-source grants totaling $143,436,162 to select organizations operating a Head Start grant in Florida, South Carolina, and Puerto Rico who demonstrated Head Start services in the affective areas were either disrupted or impacted by Hurricanes Fiona and Ian. These awards are for necessary expenses directly related to the consequences of Hurricanes Fiona and Ian, including replacement of damaged or destroyed property and facilities, and increased mental health support.

NIMH - National Institute of Mental Health

Problems in cooperating with others define antagonism, a transdiagnostic dimension of psychopathology expressed in personality and externalizing disorders. People high on antagonism are prone to aggressive, callous, and exploitative behaviors that damage relationships and incur substantial costs in the form of productivity loss, substance misuse, and criminality. While clinical theories link antagonism to deficits in social cognition, it is hard to deny that exploiting others requires an understanding of their mind. This apparent contradiction can be resolved by distinguishing between two facets of antagonism: callousness and exploitativeness. Our prior work and preliminary data inform the hypothesis that exploitativeness reflects an enhanced capacity to learn about the mental states and behaviors of others coupled with an increased sensitivity to personal, rather than shared, rewards. In contrast, callousness reflects a broader insensitivity to social feedback. We hypothesize that these dissociable social learning processes are instantiated in canonical circuits that expanded during anthropogenesis to support mentalizing and self-directed thought. These learning signals, which track behaviorally salient features of the social environment, are integrated in the posterior hub of the default network where they drive adaptive cooperation. We will test these hypotheses in two samples elevated on antagonism. At the behavioral level, we will characterize participants using a battery of personality and psychopathology measures, social and reward-based decision-making tasks, and corresponding hierarchically estimated reinforcement learning models (Aim 1). In a model-based fMRI study of our existing longitudinal clinical cohort, we will link model-derived learning signals and facets of antagonism to underlying neural activity during cooperative decision-making (Aim 2). Leveraging the multi-timescale design of our study, we will relate neurocomputational signatures of callousness and exploitativeness to mentalizing abilities, multi- informant reports of momentary interpersonal behavior, and prospective stress generation. The interdisciplinary investigative team assembled for this project has expertise in quantitative models of personality and psychopathology (Allen, Pilkonis), interpersonal theory (Allen, Pilkonis, Hallquist), experimental design (Dombrovski, FeldmanHall), social computational neuroscience (Allen, Dombrovski, Hallquist, FeldmanHall), imaging methods (Hallquist), multi-informant ecological momentary assessment (Pilkonis), and stress generation (Allen, Slavich). In line with the NIMH’s Strategic Objectives, the proposed work will reveal the brain mechanisms underlying critical social processes and characterize neural circuit mechanisms that contribute to human behavior and psychopathology. Our approach bridges modern dimensional models of psychopathology with the RDoC framework, integrating across multiple levels of analysis to elucidate human social processes, and shed light on the ways we perceive and understand others.

NIGMS - National Institute of General Medical Sciences

PROJECT SUMMARY/ABSTRACT Since the first NARCH program more than 20 years ago, ANTHC has increased its capacity to conduct research and supports research in many ways, including a Research Services Department, the Board Subcommittee HRRC overseeing research review and approval, and the Research Consultation Committee providing input throughout the research design, conduct, and dissemination. Despite significant gains in research capacity and infrastructure the need for advancing tribal research priorities that are reflective of identified health research needs remains, especially as AN people continue to experience challenges to health and wellbeing. At the same time, there is an increasing demand for growing a strong and skilled research workforce from tribally recognized tribes as well as non-tribal members who are educated and trained in tribally-driven research. ANTHC is committed to being a NARCH Center of excellence that offers meaningful and intentional career development, enhancement and mentorship opportunities in conjunction with research projects that engage and partner with tribes and communities statewide through relationships that have been established over many years or newly formed collaborations. The research projects in this overall NARCH focus on the impact of a micronutrient on mental health, improving access to physical therapy through telemedicine and developing a culturally-grounded stress coping intervention to improve urogenital health outcomes. ANTHC developed the overall NARCH center to address tribal health concerns as well as gaps in research capacity, specifically training and career enhancement, incorporating indigenous ways of knowing with western research methods, mentoring networks, and continuing to do this important work in partnerships with tribal and tribal-serving organizations. The proposed NARCH Center leverages ANTHC’s strengths with the unique research needs and landscape of Alaska and expands existing partnerships to continue improving research, career development and capacity building efforts. Thus, the overall goal is continue advancing Alaska Native health research priorities through two Career Enhancement Projects (CEPs) and three Research Projects (RPs) in pursuit of ANTHC’s vision that Alaska Native people are the healthiest people in the world. To achieve this goal, we propose the following overall specific aims: 1. Increase career enhancement opportunities in health research for Alaska Native tribes and tribal members as well as those working with and for tribes or tribal serving organizations. 2. Conduct tribally-driven health research focused on addressing health outcomes in priority areas to improve the health of Alaska Native people overall.

Education Department

The Department of Education (Department) is issuing a notice inviting applications for new awards for fiscal year (FY) 2025 funds for the Mental Health Service Professional Demonstration Grant program (MHSP).

Education Department

The Department of Education (Department) is issuing a notice inviting applications for new awards for fiscal year (FY) 2025 funds for the School-Based Mental Health Services Grant program (SBMH).

NIAAA - National Institute on Alcohol Abuse and Alcoholism

ABSTRACT The Alcohol Research Consortium in HIV Center for Research at the Intersection of Equity, Alcohol, Community and HIV (ARCH REACH) seeks to optimize well-being among PWH and accelerate progress towards Ending the HIV Epidemic (EHE) by addressing co-occurring unhealthy alcohol use (UAU). Grounded in health equity and with careful attention to social and structural drivers of health, we will expand the scope and relevance of scientific knowledge and treatment interventions at the intersection of the HIV Care Continuum, the Alcohol Care Continuum, and HIV-related comorbidities. We will do this by developing, tailoring, and implementing evidence- based interventions (EBIs) for alcohol reduction that are accessible to PWH with UAU; addressing syndemic conditions in our intervention, implementation, and epidemiology work; actively engaging PWH with diverse lived experiences in our Center; and expanding the diversity and inclusion of project researchers and trainees. Our scientific goals are to: 1) increase the reach of alcohol EBIs through implementation science and epidemiological research at the intersection of UAU and HIV, 2) expand our HIV research to incorporate new definitions of alcohol use disorder recovery, and 3) increase inclusivity/diversity of perspectives in ARCH REACH through community engagement and mentoring of trainees. We propose a highly interactive and synergistic Center with three projects supported by Administrative, Methods, and Dissemination Cores. ARCH REACH is embedded in and capitalizes on the research and clinical infrastructure of the Center for AIDS Research Network of Integrated Clinical Systems (CNICS), a multi-site clinical cohort representing ten university-based HIV clinics across the United States (US)—with many located in high priority regions for EHE. The first project leverages CNICS data to examine the relationship between UAU, UAU treatments, and new definitions of AUD recovery on HIV treatment outcomes and comorbidities among PWH in the context of social determinants of health. Our second project, using human centered design methods, will adapt, tailor, and pilot test an alcohol EBI for telephone delivery in a Hybrid Type 1 Effectiveness-Implementation study. Lastly, our third project, a Hybrid Type 2 Effectiveness-Implementation design, will tailor and implement a syndemic conditions intervention for UAU and co-occurring mental health disorders using an AUDIT and Feedback implementation strategy. An Administrative Core will provide the structure and processes to support collaboration and synergy across ARCH REACH projects and investigators. A Methods Core will support implementation science aims of projects and develop novel analytic methods. Lastly, a Dissemination Core will assemble a Transdisciplinary Community Partner Board and support the dissemination of project findings to ensure the equitable uptake, receipt, and delivery of EBIs for UAU. Capitalizing on a strong organizational structure, the extensive resources and infrastructure of CNICS, and a transdisciplinary team inclusive of community members, ARCH REACH addresses issues of high relevance to US EHE goals by addressing the intersection of HIV, alcohol use, and health equity.

NIMH - National Institute of Mental Health

Project Summary/Abstract It is well established that inflammatory markers are increased in individuals with stress-related psychiatric disorders and can contribute to their pathology. However, we lack a thorough understanding of the circuits, receptors, and transcriptional mechanisms driving these inflammatory processes in the brain and how they might differ in males and females. Stress activates the canonical “fight or flight” sympathetic nervous system, which uses noradrenaline as a neurotransmitter. Noradrenaline activates nuclear factor kappa B (NFkB), a master transcriptional regulator of inflammatory genes, to increase inflammation in peripheral immune cells. Stress also activates the locus coeruleus (LC), the primary source of noradrenaline in the brain. However, it is unknown whether the LC increases pro-inflammatory NFkB-mediated transcription in the hippocampus, a brain region that controls stress-related behaviors and is prone to stress-induced inflammatory processes. We found 1) 10 days of chronic social defeat stress (CSDS) increases nuclear NFkB in the hippocampus of males and females, 2) overall levels of NFkB are higher in females compared to males, suggesting it might be primed to transcribe inflammatory transcripts more readily, 3) compared to female in metestrus, females in proestrus transcribe more genes known to regulated by NFkB, which might be because the female LC is particularly sensitive to the neuroendocrine stress response, which is active during proestrus, and 4) daily administration of the α1 adrenergic receptor (α1-AR) antagonist prazosin prior to daily CSDS prevents reductions in sociability normally caused by CSDS, a stress paradigm that increases pro-inflammatory effects in the hippocampus. We hypothesize that inhibiting α1-ARs promotes sociability by mitigating inflammatory processes normally caused by CSDS. Our central hypothesis is that stress-induced noradrenergic neurotransmission increases NFkB- mediated inflammatory transcription in the hippocampus to reduce sociability. In Aim 1, we will determine whether chemogenetically inhibiting the LC throughout stress mitigates NFkB-mediated transcription in the hippocampus of males and females. We predict that the inhibitory Designer Receptor Exclusively Activated by Designer Drug (DREADD), hM4D, in noradrenergic LC neurons will increase subsequent sociability in a social interaction paradigm and reduce the transcription of a pre-defined set of transcripts regulated by NFkB, which we will identify using RNA-sequencing in hippocampal tissue. In Aim 2, we will determine whether five days of systemic administration of the α1 adrenergic receptor agonist, cirazoline, is sufficient to drive NFkB-mediated transcription in hippocampal microglia in males and estrus cycle-tracked females in metestrus or proestrus. We predict that cirazoline will increase nuclear NFKB in hippocampal microglia and neurons and increase NFkB- mediated transcripts in hippocampal microglia, with the strongest effects in females in proestrus. This project is highly conducive to undergraduates, who have already demonstrated they can successfully complete most assays described in this proposal.