Signatures of hierarchical temporal processing in the mouse visual system.

Autor: Rudelt L; Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany.; Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany., González Marx D; Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany.; Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany., Spitzner FP; Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany.; Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany., Cramer B; Kirchhoff-Institute for Physics, Heidelberg University, Heidelberg, Germany., Zierenberg J; Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany.; Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany., Priesemann V; Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany.; Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany.; Bernstein Center for Computational Neuroscience (BCCN), Göttingen, Germany.
Jazyk: angličtina
Zdroj: PLoS computational biology [PLoS Comput Biol] 2024 Aug 22; Vol. 20 (8), pp. e1012355. Date of Electronic Publication: 2024 Aug 22 (Print Publication: 2024).
DOI: 10.1371/journal.pcbi.1012355
Abstrakt: A core challenge for the brain is to process information across various timescales. This could be achieved by a hierarchical organization of temporal processing through intrinsic mechanisms (e.g., recurrent coupling or adaptation), but recent evidence from spike recordings of the rodent visual system seems to conflict with this hypothesis. Here, we used an optimized information-theoretic and classical autocorrelation analysis to show that information- and correlation timescales of spiking activity increase along the anatomical hierarchy of the mouse visual system under visual stimulation, while information-theoretic predictability decreases. Moreover, intrinsic timescales for spontaneous activity displayed a similar hierarchy, whereas the hierarchy of predictability was stimulus-dependent. We could reproduce these observations in a basic recurrent network model with correlated sensory input. Our findings suggest that the rodent visual system employs intrinsic mechanisms to achieve longer integration for higher cortical areas, while simultaneously reducing predictability for an efficient neural code.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2024 Rudelt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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