CELLMAPR: INFERRING CELL IDENTITY FROM WHOLE-BRAIN IMAGING DATA

Understanding how distributed neuronal populations give rise to brain function requires linking molecular cell identity with brain-wide patterns of activity. Light-sheet fluorescence microscopy (LSFM) enables imaging of intact cleared brains at single-cell resolution, capturing activity-dependent signals across the central nervous system. In parallel, spatial transcriptomic atlases describe the distribution of transcriptionally defined cell types throughout the mouse brain. Despite these advances, whole-brain imaging lacks molecular identity, whereas transcriptomic atlases lack direct functional context.

Here we present CellMapR, a computational framework for cell-type inference from volumetric whole-brain imaging data. CellMapR integrates LSFM-derived activity maps with spatial transcriptomic references using spatial density modeling and probabilistic mapping. By assessing spatial correspondence between observed activity patterns and transcriptomically defined cell-type distributions, CellMapR produces local estimates of underlying cellular composition, yielding whole-brain predictions of putative contributing cell types.

We demonstrate the framework using in-house generated whole-brain LSFM datasets of neuronal activity following administration of Semaglutide, a GLP-1 receptor agonist used to treat obesity and diabetes. CellMapR identifies region- and cell-type–specific recruitment across the mouse brain, highlighting neuronal subsets enriched for GLP-1R–related signaling components. These results provide a refined cellular view of drug-evoked brain activity and illustrate how pharmacological effects can be decomposed into candidate cellular substrates in silico.

More broadly, CellMapR enables data-driven exploration of whole-brain cell-type organization, rational target selection for stereotaxic manipulation, interpretation of neural substrates underlying behavior, and mechanistic dissection of drug mode of action, establishing a scalable approach for functional cell-type mapping at whole-brain scale.