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Signatures of hierarchical temporal processing in the mouse visual system

MPG-Autoren
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Rudelt,  Lucas
Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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González Marx,  Daniel
Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Spitzner,  F. Paul
Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Zierenberg,  Johannes
Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Priesemann,  Viola
Max Planck Research Group Complex Systems Theory, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Zitation

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.


Zitierlink: https://hdl.handle.net/21.11116/0000-000F-CD8B-E
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.