Population-level temporal decoding and dynamical structure in frontostriatal circuits during decision making
Adam B. GoldringiD, Anandita De, Tanner StevensoniD, Kendall Stewart, Aya Akhmetzhanova, Rishidev ChaudhuriiD, Timothy D. HanksiD
Abstract
Perceptual decisions unfold over time, requiring neural circuits to evaluate sensory evidence, track elapsed time, and commit to an action. To investigate how these computations are distributed across corticostriatal circuits, we recorded large-scale neural population activity using Neuropixels probes in the rat frontal orienting field (FOF) and anterior dorsal striatum (ADS) during a free-response auditory change detection task. Both regions exhibited structured, highly dynamic population activity during task performance. Using single-trial population decoding, we found that both FOF and ADS robustly encoded retrospective time from stimulus onset and prospective time preceding the decision report. Using a new approach to analyze temporal encoding to identify the dynamical structure supporting decoding, we found that time encoding could be decomposed into two primary dynamical motifs: monotonic ramp-like trajectories and transient bump-like trajectories. While these modes were similarly expressed during early evidence evaluation, FOF exhibited more pronounced decision-aligned changes near the time of the decision report, possibly reflecting a state transition at commitment. Population geometry analyses further revealed stable low-dimensional subspaces during evidence evaluation that transitioned at decision commitment, with significantly larger subspace changes in FOF than ADS. Together, these results reveal a common dynamical framework during evidence evaluation across corticostriatal circuits, while identifying a selective reorganization of FOF dynamics associated with decision commitment.
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