ArticlebioRxiv : the preprint server for biology2025
How cortico-basal ganglia-thalamic subnetworks can shift decision policies to maximize reward rate.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
All mammals exhibit flexible decision policies that depend, at least in part, on the cortico-basal ganglia-thalamic (CBGT) pathways. Yet understanding how the complex connectivity, dynamics, and plasticity of CBGT circuits translate into experience-dependent shifts of decision policies represents a longstanding challenge in neuroscience. Here we present the results of a computational approach to address this problem. Specifically, we simulated decisions driven by CBGT circuits under baseline, unrewarded conditions using a spiking neural network, and fit an evidence accumulation model to the resulting behavior. Using canonical correlation analysis, we then replicated the identification of three control ensembles (
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