Funding Opportunity Number: RFA-DA-25-023
Deadline: February 21, 2024
Scientific Gap and Opportunity
Research conducted over the last decade has established that essential features of substance-related experiences (e.g., rewarding properties of substances, context and contingencies of exposures and motivational states) are encoded through coordinated firing activity of neural ensembles, which are sparse, comprised of a mosaic of cells from distinct classes, and broadly distributed across the brain. Cell autonomous mechanisms and population-level rules driving the recruitment and plasticity of cells within substance-associated ensembles remain largely unknown. Addressing this gap requires the reliable measurement of cell-resolved activity dynamics during behavior and its annotation with molecular, biophysical and cytoarchitectonic information, collected ex-vivo from the same cells. Accomplishing this multimodal integration presents a number of significant technical and computational challenges that have hindered progress.
Fortunately, the growing availability of platforms enabling robust longitudinal tracking of cell dynamics in behaving animals performing Substance Use Disorder (SUD)-relevant tasks, the progress of omics-based cellular inventories and atlases, such as references developed by the BRAIN initiative cell census network (BICCN) and the National Institute on Drug Abuse (NIDA) SCORCH programs, and the growing availability of tools for targeted cell access, offer opportunities to accelerate the understanding of neural coding principles in models of substance exposure.
Research Objectives
This funding opportunity announcement aims to support synergistic research programs that employ innovative scalable technologies and leverage public cell atlases/registries to profile, identify, and map cellular ensembles that are recruited and/or undergo plasticity across different behavioral states, contexts or associative processes linked to addictive substance exposure (acute or chronic exposure, abstinence, craving, relapse, withdrawal). Emphasis is on approaches that enable robust multimodal integration of cell activity dynamics in substance-modulated cell ensembles with other data modalities encompassing cell molecular identity/states, spatial distribution, or connectivity, captured through scalable methods, with single-cell resolution.
Find more information at the opportunity website.