A shared manifold for scalable temporal representations in self-paced timing

Authors

Serrano, M., Castelli, M., Peng, Y., Sharott, A., Dupret, D.

Abstract

Adaptive behaviour often relies on tracking the passage of time, yet how distinct brain regions generate coherent temporal representations remains unclear. Using a self-paced interval timing task in mice, we show that heterogeneous single-neuron temporal firing profiles distributed across regions are organized within a shared ring manifold. Within this low-dimensional space, population activity evolves along a common trajectory across different intervals and encodes elapsed time in a relative reference frame. Different durations are not represented by separate neural states, but by modulation of traversal speed. These scalable dynamics arise from coordinated population-wide co-scaling of single-neuron activity and support trial-by-trial adjustments in timing behaviour. A cross-regional assembly of start neurons predicts, at interval onset, upcoming waiting duration and behavioural adjustments, linking initial population states to trajectory evolution. Together, these findings identify population traversal of a shared activity manifold as a mechanism for scalable temporal representation across brain regions.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 09 Sep 2026.

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