Computational Approaches in Fundamental Neuroscience

Computational Approaches in Fundamental Neuroscience is sponsored by National Institute on Aging (NIA). The National Institute on Aging (NIA) is interested in fundamental neuroscience research that harnesses computational approaches to study brain aging, Alzheimer's Disease (AD), and AD-related dementias (ADRD) across molecules, cells, and circuits and to enable development of mec…

Computational Approaches in Fundamental Neuroscience | Grants & Funding U.S. Department of Health and Human Services National Institutes of Health Computational Approaches in Fundamental Neuroscience When beginning your next investigator-initiated application, consider the following NIH highlighted topic. The area of science described below is of interest to the listed NIH Institutes, Centers, and Offices (ICOs).

This is not a notice of funding opportunity (NOFO). Apply through an appropriate NIH Parent Funding Announcement or another broad NIH opportunity available on Grants. gov .

Learn how to interpret and use Highlighted Topics . Post Date: January 27, 2026 Expiration Date: January 27, 2028 This topic aims to promote the integration of computational approaches into fundamental neuroscience research.

It encourages rigorous, hypothesis-driven multidisciplinary research to interrogate the molecular and cellular mechanisms underlying the structure and function of brain cells and neural circuits, in health and disease and across the lifespan.

Such studies can begin to model the complex spatiotemporal interactions between receptors, ion channels, enzymes, and other signaling intermediates toward the goals of uncovering mechanistic links across biological scales. The use of biophysically based models of molecular pathways, cellular processes, and morphology is encouraged, as are machine learning (ML) and artificial intelligence (AI) algorithms.

Integration of computational approaches with precise, state-of-the-art in vitro, ex vivo, or in vivo experimental paradigms, which offer high spatial and/or temporal resolution for measurement and manipulation of molecular and cellular processes, is strongly encouraged. Also, this topic promotes the creation of advanced open-source analytical tools that will be made available to researchers in academia and industry.

Interdisciplinary collaboration, fostering partnerships between investigators with complementary theoretical/computational and experimental neuroscience expertise is strongly encouraged. Such collaborations can drive innovative research and address scientific and technical challenges that might otherwise be intractable.

National Institute of Mental Health (NIMH) The National Institute of Mental Health (NIMH) is interested in research that applies computational approaches to fundamental neuroscience research investigating the molecular and cellular mechanisms that drive the structure and function of cells and circuits supporting cognitive, affective, and social domains.

Collaborations between investigators with complementary computational and experimental expertise and development of open-source tools is encouraged. Areas of interest under this topic include, but are not limited to: Predicting protein sequence-structure-function-interaction relationships. Elucidating spatiotemporal dynamics of molecular and cellular processes in neurons and glia.

Understanding factors regulating cellular morphology and its impact on function. Illuminating mechanisms of synaptic transmission and plasticity. Mapping developmental trajectories across molecular and cellular scales.

Yael Mandelblat-Cerf, PhD National Center for Complementary and Integrative Health (NCCIH) The NCCIH supports the development of computational methods and tools that include complementary and integrative health approaches for improving diagnosis, prevention, or treatment of diseases and symptoms, and promoting well-being and whole person health.

Emphasis is on integrating computational methods into neuroscience research and therapeutics development. This includes using biophysically based models, machine learning (ML), and artificial intelligence (AI) algorithms. Integration with advanced experimental paradigms for precise measurement and manipulation of molecular and cellular processes is encouraged.

This topic supports interdisciplinary collaboration and the creation of open-source analytical tools. Additionally, NCCIH supports multisystem studies to understand brain and nervous system interactions, including interoception, and the impact of multi-component interventions in pre-clinical models and/or human subjects. Emrin Horgusluoglu, Ph.

D. National Eye Institute (NEI) James (Shaojian) Gao, Ph. D.

National Institute on Aging (NIA) NIA is interested in fundamental neuroscience research that harnesses computational approaches to study brain aging, Alzheimer’s Disease (AD), and AD-related dementias (ADRD) across molecules, cells, and circuits and to enable development of mechanistic models of aging for motor, sensory, cognitive, affective, and social behavior.

Secondary use of existing data and interdisciplinary collaborations involving both experimental and computational researchers are encouraged.

Areas of interest under this topic include, but are not limited to: Integrating multimodal data across spatial-temporal scales Uncovering mechanisms of selective vulnerability and resilience Examining aging processes (including the hallmarks of aging) and their contributions to AD/ADRD Investigating changes in synaptic plasticity and network activity Characterizing brain aging trajectories Developing causal, multiscale models of molecular targets and disease pathways for use in data-driven therapy development National Institute on Drug Abuse (NIDA) NIDA is interested in supporting research and development of computational approaches and AI/ML tools to understand the neurobiological mechanisms of substance use disorder (SUD) at the molecular, cellular, circuit and system levels; how they are associated with initiation, progression, and recovery from the disorder; and to identify new targets and compounds for its treatment.

It includes but is not limited to the design of new medication candidates, virtual screening of compound libraries, as well as predictive pharmacokinetics/absorption, distribution, metabolism, and excretion (ADME), drug-drug interaction (DDI), safety profiles, and dose selection of new potentially therapeutic compounds.

Office of Research on Women's Health (ORWH) The NIH Office of Research on Women's Health (ORWH) areas of interest include: Utilize computational approaches to model and understand the unique molecular and cellular mechanisms underlying women's brain health, considering hormonal influences and sex-specific neural circuitry across the life course.

Integrate computational methods with precise experimental paradigms offering high spatial and/or temporal resolution, to study female-specific molecular and cellular processes, and accelerate the discovery and development of therapeutics for women's brain health.

Foster interdisciplinary collaboration to develop advanced open-source analytical tools and cutting-edge computational technologies to facilitate screening, prevention, diagnosis, and treatment of diseases affecting women. This office does not award grants. Applications must be relevant to the objectives of at least one of the participating NIH Institutes and Centers listed in this topic.

Elena Gorodetsky, M. D. , Ph.

D. For technical issues E-mail OER Webmaster