The broad goal of The BRAIN InitiativeSMis to understand the circuits and patterns of neural activity that give rise to mental experience and behavior. As stated in the BRAIN 2025 Report (II.5), "Theory, Modeling, and Statistics Will Be Essential to Understanding the Brain." As advances in neurotechnologies are producing large, complex datasets at an unprecedented rate, novel theoretical and analytical approaches are needed to realize the potential of these rich datasets. Understanding neural circuitry requires an understanding of the algorithms and mechanisms that govern information processing within and between interacting circuits in the brain as a whole. Informed by rich observations, formalized theoretical frameworks allow researchers to infer general principles of brain function and the algorithms underlying functioning neural circuitry. Theory coupled with mathematical modeling and simulations are needed to identify gaps in knowledge, to drive the systematic collection of the future data (e.g., collected data should address model parameters that are currently unknown), and to formulate testable hypotheses on neural circuit mechanisms and how they affect behavioral and cognitive processes. Statistical approaches are needed to conduct formal inference to support or refute a stated theory or hypothesis. Finally, new data analysis methods, including Artificial Intelligence and Machine Learning (AI/ML) methods, are needed to detect dynamical features and patterns in complex data, often spanning multiple modalities and scales, are needed to reveal underlying mechanisms of brain function.
This reissue has been updated based on the recommendations of the BRAIN Initiative 2.0 report:
For this reissue, priority will be given to the development of:
Analytical and computational tools to facilitate new theory development as well as tools to integrate existing (especially competing) theories, and conceptual frameworks
Multiscale/Multiphysics models incorporating biologically-inspired dynamical representations of neurons mechanistically linking to behavioral processes
Platforms incorporating machine-driven knowledge integration of competing theories for the discovery of foundational theories of the brain
Projects are encouraged to utilize the NIH BRAINWORKS platform (that organizes, integrates, and represents nuanced knowledge contained within the growing body of the scientific literature) to assist in the development of Theories, Models and Methods for understanding brain circuits from the cellular and subsecond resolution to behavior.
Awards:
Application budgets are not limited, but are expected to range between $150,000 to $250,000 direct costs per year. Investigators are expected to request a budget that is required to accomplish the proposed work.
Letter of Intent:
30 days before application due date
Full Proposal Submission Deadline:
December 15, 2022
Contacts:
Susan N. Wright, PhD, National Institute on Drug Abuse (NIDA), Telephone: 301-402-6683
Email: BRAINTheoriesFOA@mail.nih.gov
