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  Signatures of hierarchical temporal processing in the mouse visual system

Rudelt, L., González Marx, D., Spitzner, F. P., Cramer, B., Zierenberg, J., & Priesemann, V. (2024). Signatures of hierarchical temporal processing in the mouse visual system. PLOS Computational Biology, 20(8): e1012355. doi:10.1371/journal.pcbi.1012355.

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 Urheber:
Rudelt, Lucas1, Autor           
González Marx, Daniel1, Autor           
Spitzner, F. Paul1, Autor           
Cramer, Benjamin, Autor
Zierenberg, Johannes1, Autor           
Priesemann, Viola1, Autor           
Affiliations:
1Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2616694              

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 Zusammenfassung: 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.

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Sprache(n): eng - English
 Datum: 2024-08-22
 Publikationsstatus: Online veröffentlicht
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1371/journal.pcbi.1012355
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Titel: PLOS Computational Biology
  Kurztitel : PLOS Comput Biol
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: 31 Band / Heft: 20 (8) Artikelnummer: e1012355 Start- / Endseite: - Identifikator: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1