The dynamics and geometry of choice in the premotor cortex

Mikhail Genkin, Krishna V. Shenoy, Chandramouli Chandrasekaran and Tatiana A. Engel ()
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Mikhail Genkin: Cold Spring Harbor Laboratory
Krishna V. Shenoy: Stanford University
Chandramouli Chandrasekaran: Boston University
Tatiana A. Engel: Cold Spring Harbor Laboratory

Nature, 2025, vol. 645, issue 8079, 168-176

Abstract: Abstract The brain represents sensory variables in the coordinated activity of neural populations, in which tuning curves of single neurons define the geometry of the population code1,2. Whether the same coding principle holds for dynamic cognitive variables remains unknown because internal cognitive processes unfold with a unique time course on single trials observed only in the irregular spiking of heterogeneous neural populations3–8. Here we show the existence of such a population code for the dynamics of choice formation in the primate premotor cortex. We developed an approach to simultaneously infer population dynamics and tuning functions of single neurons to the population state. Applied to spike data recorded during decision-making, our model revealed that populations of neurons encoded the same dynamic variable predicting choices, and heterogeneous firing rates resulted from the diverse tuning of single neurons to this decision variable. The inferred dynamics indicated an attractor mechanism for decision computation. Our results reveal a unifying geometric principle for neural encoding of sensory and dynamic cognitive variables.

Date: 2025
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DOI: 10.1038/s41586-025-09199-1

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