Information-theoretic gradient flows in mouse visual cortex

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F25%3A00082250" target="_blank" >RIV/00159816:_____/25:00082250 - isvavai.cz</a>

Result on the web

<a href="https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2025.1700481/full" target="_blank" >https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2025.1700481/full</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fninf.2025.1700481" target="_blank" >10.3389/fninf.2025.1700481</a>

Result language

angličtina

Original language name

Information-theoretic gradient flows in mouse visual cortex

Original language description

Introduction Neural activity can be described in terms of probability distributions that are continuously evolving in time. Characterizing how these distributions are reshaped as they pass between cortical regions is key to understanding how information is organized in the brain.Methods We developed a mathematical framework that represents these transformations as information-theoretic gradient flows - dynamical trajectories that follow the steepest ascent of entropy and expectation. The relative strengths of these two functionals provide interpretable measures of how neural probability distributions change as they propagate within neural systems. Following construct validation in silico, we applied the framework to publicly available continuous Delta F/F two-photon calcium recordings from the mouse visual cortex.Results The analysis revealed consistent bi-directional transformations between the rostrolateral area and the primary visual cortex across all five mice. These findings demonstrate that the relative contributions of entropy and expectation can be disambiguated and used to describe information flow within cortical networks.Discussion We introduce a framework for decomposing neural signal transformations into interpretable information-theoretic components. Beyond the mouse visual cortex, the method can be applied to diverse neuroimaging modalities and scales, thereby providing a generalizable approach for quantifying how information geometry shapes cortical communication.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

30103 - Neurosciences (including psychophysiology)

Project

<a href="/en/project/NW25-04-00226" target="_blank" >NW25-04-00226: Enhancing epilepsy treatment with temporal interference of electric fields and advanced computational strategies</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Frontiers in Neuroinformatics

ISSN

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e-ISSN

1662-5196

Volume of the periodical

19

Issue of the periodical within the volume

Oct 2025

Country of publishing house

CH - SWITZERLAND

Number of pages

8

Pages from-to

1700481

UT code for WoS article

001613675200001

EID of the result in the Scopus database

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