Firing rates in visual cortex show representational drift, while temporal spike sequences remain stable

Neural firing-rate responses to sensory stimuli show progressive changes both within and across sessions, raising the question of how the brain maintains a stable code. One possibility is that other features of multi-neuron spiking patterns, e.g., the temporal structure, provide a stable coding mechanism. Here, we compared spike-rate and spike-timing codes in neural ensembles from six visual areas during natural video presentations. To quantify information in spike sequences, we used SpikeShip, a method based on the optimal transport theory that considers the relative spike-timing relations among all neurons. For large numbers of active neurons, temporal spike sequences conveyed more information than population firing-rate vectors. Firing-rate vectors exhibited substantial drift across repetitions and between blocks, in contrast to spike sequences, which were stable over time. These findings reveal a stable neural code based on relative spike-timing relations in high-dimensional neural ensembles.

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Publication Details

Journal
Cell Reports
Published
2025-04-01
DOI
https://doi.org/10.1016/j.celrep.2025.115547
Citations
9
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
11.45

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article

Firing rates in visual cortex show representational drift, while temporal spike sequences remain stable

Francesco P. Battaglia, Boris Sotomayor-Gómez, Martin Vinck
9 citations
Cell Reports
Neural dynamics and brain function
11.45
article

Firing rates in visual cortex show representational drift, while temporal spike sequences remain stable

Francesco P. Battaglia, Boris Sotomayor-Gómez, Martin Vinck
article en
9 citations

Abstract

Neural firing-rate responses to sensory stimuli show progressive changes both within and across sessions, raising the question of how the brain maintains a stable code. One possibility is that other features of multi-neuron spiking patterns, e.g., the temporal structure, provide a stable coding mechanism. Here, we compared spike-rate and spike-timing codes in neural ensembles from six visual areas during natural video presentations. To quantify information in spike sequences, we used SpikeShip, a method based on the optimal transport theory that considers the relative spike-timing relations among all neurons. For large numbers of active neurons, temporal spike sequences conveyed more information than population firing-rate vectors. Firing-rate vectors exhibited substantial drift across repetitions and between blocks, in contrast to spike sequences, which were stable over time. These findings reveal a stable neural code based on relative spike-timing relations in high-dimensional neural ensembles.

Cell ReportsVol. 44(4)
Radboud University Nijmegen (NL), Ernst Strüngmann Institute for Neuroscience (DE)
Deutsche Forschungsgemeinschaft, Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 1%
Neural dynamics and brain function
11.45
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