Cell-type-specific population dynamics of diverse reward computations.

ABSTRACT: Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, and computational features), we identified encoding of reward-predictive cues and reward outcomes in distinct genetically defined neural populations, including TH⁺ cells and Tac1⁺ cells. Data from genetically targeted recordings were used to train an optimized nonlinear dynamical systems model and revealed activity dynamics consistent with a line attractor. High-density, cell-type-specific electrophysiological r

SUBMITTER: Sylwestrak EL 

PROVIDER: S-EPMC10387374 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature