Invasive surgical procedures provide the unique ability to record and stimulate neurons within precisely localized brain structures in humans. Human studies using invasive technology are often constrained by a limited number of patients and resources available to implement complex experimental protocols and are rarely aggregated in a manner that addresses research questions with appropriate statistical power. Therefore, this RFA seeks applications to assemble diverse, integrated, multi-disciplinary teams that cross boundaries of interdisciplinary collaboration to overcome these fundamental barriers and to investigate high-impact questions in human neuroscience. Projects should maximize opportunities to conduct innovative in vivo neuroscience research made available by direct access to brain recording and stimulating from invasive surgical procedures. Projects should employ approaches guided by specified theoretical constructs and quantitative, mechanistic models where appropriate.

Awardees will join a consortium work group, coordinated by the NIH, to identify consensus standards of practice, including neuroethical considerations, to collect and provide data for ancillary studies, and to aggregate and standardize data for dissemination among the wider scientific community.

These RFAs will support integrated, interdisciplinary research teams from prior BRAIN technology and/or integrated approaches teams, and/or new projects from the research community that focus on examining circuit functions related to behavior, using advanced and innovative technologies. The goal will be to support programs with a team science approach that can realize meaningful outcomes within 5-plus years. Awards will be made for 5 years, with a possibility of one renewal. Projects will incorporate overarching principles of circuit function in the context of specific neural systems underlying sensation, perception, emotion, motivation, cognition, decision-making, motor control, communication, or homeostasis. Applications should incorporate theory-/model-driven experimental design and should offer predictive models as deliverables. Applications should seek to understand circuits of the central nervous system by systematically controlling stimuli and/or behavior while actively recording and/or manipulating relevant dynamic patterns of neural activity and by measuring the resulting behaviors and/or perceptions. Applications are expected to employ approaches guided by specified theoretical constructs, and are encouraged to employ quantitative, mechanistic models where appropriate. Applications will be required to manage their data and analysis methods in a prototype framework that will be developed and used in the proposed U19 project and exchanged with other BRAIN U19 awardees for further refinement and development. Model systems, including the possibility of multiple species ranging from invertebrates to humans, can be employed and should be appropriately justified. Programs should employ multi-component teams of research expertise - including neurobiologists, statisticians, physicists, mathematicians, engineers, computer scientists, and data scientists, as appropriate - that seek to cross boundaries of interdisciplinary collaboration.