Distributed context-dependent choice information in mouse posterior cortex.

ABSTRACT: Choice information appears in multi-area brain networks mixed with sensory, motor, and cognitive variables. In the posterior cortex-traditionally implicated in decision computations-the presence, strength, and area specificity of choice signals are highly variable, limiting a cohesive understanding of their computational significance. Examining the mesoscale activity in the mouse posterior cortex during a visual task, we found that choice signals defined a decision variable in a low-dimensional embedding space with a prominent contribution along the ventral visual stream. Their subspace was near-orthogonal to concurrently represented sensory and motor-related activations, with modulations by task difficulty and by the animals' attention state. A recurrent neural network trained with animal

SUBMITTER: Orlandi JG 

PROVIDER: S-EPMC9837177 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature