A transient high-dimensional geometry affords stable conjunctive subspaces for efficient action selection.

ABSTRACT: Flexible action selection requires cognitive control mechanisms capable of mapping the same inputs to different output actions depending on the context. From a neural state-space perspective, this requires a control representation that separates similar input neural states by context. Additionally, for action selection to be robust and time-invariant, information must be stable in time, enabling efficient readout. Here, using EEG decoding methods, we investigate how the geometry and dynamics of control representations constrain flexible action selection in the human brain. Participants performed a context-dependent action selection task. A forced response procedure probed action selection different states in neural trajectories. The result shows that before successful responses, there is a

SUBMITTER: Kikumoto A 

PROVIDER: S-EPMC11445473 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature