Information-theoretic gradient flows in mouse visual cortex
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.
Authors
- Erik D. Fagerholm (ORCID: https://orcid.org/0000-0003-2973-1395)
- Hirokazu Tanaka (ORCID: https://orcid.org/0000-0002-3153-8802)
- Milan Brázdil (ORCID: https://orcid.org/0000-0001-7979-2343)
Institutions
- Tokyo City University (JP)
- Masaryk University (CZ)
- St. Anne's University Hospital Brno (CZ)
Publication Details
- Journal
- Frontiers in Neuroinformatics
- Published
- 2025-10-30
- DOI
- https://doi.org/10.3389/fninf.2025.1700481
- Primary Topic
- Neural dynamics and brain function
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- Ministerstvo Školství, Mládeže a Tělovýchovy
- Masarykova Univerzita
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Core Research for Evolutional Science and Technology