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

Boris Sotomayor-Gómez, Francesco P. Battaglia, Martin Vinck

2025Cell Reports11 citationsDOIOpen Access PDF

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.

Topics & Concepts

Spike (software development)NeuroscienceVisual cortexTemporal cortexBiologyCortex (anatomy)Computer scienceSoftware engineeringNeural dynamics and brain functionVisual perception and processing mechanismsNeural Networks and Applications
Firing rates in visual cortex show representational drift, while temporal spike sequences remain stable | Litcius