Authors
Ramanujan Srinath, Yunlong Xu, Douglas A Ruff, Amy M Ni, Brent Doiron, Marlene R Cohen
Published in
Proceedings of the National Academy of Sciences of the United States of America. Volume 123. Issue 28. Pages e2523217123. Jul 14, 2026. Epub Jul 07, 2026.
Abstract
Shared trial-to-trial variability across sensory neurons is reliably reduced when perceptual performance improves, yet this variability is low dimensional, so it could be ignored by an optimal readout mechanism. Why then is it so consistently related to behavior? We propose that shared variability both reflects circuit structure and reveals the information communicated to downstream areas. In this framework, the same connectivity that shapes signal propagation also shapes shared variability. Using a circuit model, we show that when sensory signals align with shared variability, behaviorally relevant information is amplified without compromising coding fidelity. Analyses of neural population recordings from multiple brain areas and tasks reveal that the dominant axis of shared variability consistently aligns with task-relevant stimulus features and action plans. Finally, the behavioral impact of microstimulation can be explained by the extent to which it changes projections onto the shared variability axis. These findings suggest that shared variability may illuminate, rather than obscure, the neural dimensions that guide behavior.
PMID:
42412944
Bibliographic data and abstract were imported from PubMed on 08 Jul 2026.
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