Transitions in dynamical regime and neural mode during perceptual decisions

Thomas Zhihao Luo, Timothy Doyeon Kim, Diksha Gupta, Adrian G. Bondy, Charles D. Kopec, Verity A. Elliott, Brian DePasquale, Carlos D. Brody

Research output: Contribution to journalArticlepeer-review

Abstract

Perceptual decision-making is thought to be mediated by neuronal networks with attractor dynamics1,2. However, the dynamics underlying the complex neuronal responses during decision-making remain unclear. Here we use simultaneous recordings of hundreds of neurons, combined with an unsupervised, deep-learning-based method, to discover decision-related neural dynamics in the rat frontal cortex and striatum as animals accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes: an initial phase dominated by sensory inputs, followed by a phase dominated by autonomous dynamics, with the flow direction (that is, neural mode) largely orthogonal to that in the first regime. We propose that this transition marks the moment of decision commitment, that is, the time when the animal makes up its mind. To test this, we developed a simplified model of the dynamics to estimate a putative neurally inferred time of commitment (nTc) for each trial. This model captures diverse single-neuron temporal profiles, such as ramping and stepping3,4. The estimated nTc values were not time locked to stimulus or response timing but instead varied broadly across trials. If nTc marks commitment, evidence before this point should affect the decision, whereas evidence afterwards should not. Behavioural analysis aligned to nTc confirmed this prediction. Our findings show that decision commitment involves a rapid, coordinated transition in dynamical regime and neural mode and suggest that nTc offers a useful neural marker for studying rapid changes in internal brain state.

Original languageEnglish (US)
Pages (from-to)1156-1166
Number of pages11
JournalNature
Volume646
Issue number8087
DOIs
StatePublished - Oct 30 2025

All Science Journal Classification (ASJC) codes

  • General

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