Editorial: Bridging computation, biophysics, medicine, and engineering in neural circuits
hardware, bioengineering, and medicine. A unifying theme across these works is the investigation of 32 how structured dynamics and learning rules enable robust information processing, cognition, and 33 recovery from damage in biological neural systems, as well as how these principles can guide the 34 development of computational and neuroengineering models. 35Several studies in this Research Topic focus on recurrent network dynamics as a foundation for 36 cortical information processing. Yonemura and Katori extended reservoir computing-based cortical 37 models to account for multi-sensory integration. By combining predictive coding with reliability-38 weighted error feedback, their model allows a recurrent reservoir to extract temporal context while 39 dynamically adjusting the influence of each sensory modality depending on its noise level.
Authors
- Haruyuki Kamiya (ORCID: https://orcid.org/0000-0002-2618-3146)
- Hideaki Yamamoto (ORCID: https://orcid.org/0000-0003-3362-5376)
- Toshiaki Omori (ORCID: https://orcid.org/0000-0003-4011-0055)
- Shigeo Sato (ORCID: https://orcid.org/0000-0003-3912-357X)
- Juan José Soriano
Institutions
- Tohoku University (JP)
- Hokkaido University (JP)
- Institute of Neurobiology (BG)
- Kobe University (JP)
- Universitat de Barcelona (ES)
Publication Details
- Journal
- Frontiers in Neural Circuits
- Published
- 2026-01-21
- DOI
- https://doi.org/10.3389/fncir.2026.1776224
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministerio de Ciencia, Innovación y Universidades
- European Commission
- Generalitat de Catalunya
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Research Institute of Electrical Communication, Tohoku University
- European Regional Development Fund
- Agencia Estatal de Investigación
- Core Research for Evolutional Science and Technology