ORIGINAL RESEARCH article
Front. Neurosci.
Sec. Neuromorphic Engineering
Volume 19 - 2025 | doi: 10.3389/fnins.2025.1678035
This article is part of the Research TopicNeuromorphic computing and chaotic neural networksView all articles
Network Topological Reorganization Mechanisms of Primary Visual Cortex Under Multimodal Stimulation
Provisionally accepted
- 1National University of Defense Technology, Changsha, China
- 2Hunan Normal University, Changsha, China
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The functional connectivity network of the primary visual cortex (V1) is fundamental to sensory processing and cross-modal integration. The topological architecture of these neural networks—defined by modularity and the distribution of hub nodes—profoundly influences information flow and computational efficiency. Despite this, the impact of different sensory modalities on V1 network topology remains poorly understood.} Here, we hypothesized that multimodal sensory input would drive systematic reorganization of V1 functional network properties. Leveraging in vivo two-photon calcium imaging of mouse V1 under unimodal visual (V) and bimodal visual-tactile (V+T) stimulation, together with comprehensive functional connectivity mapping and graph-theoretical analysis, we found that: (1) Unimodal stimulation selectively increased betweenness centrality, reinforcing modular processing and local information control through prominent hub nodes; (2) Bimodal stimulation facilitated global network integration, as evidenced by elevated closeness centrality, broadened connectivity, and enhanced transmission efficiency, accompanied by a marked reduction in modularity; (3) Under unimodal conditions, the top five centrality nodes exhibited significantly stronger calcium responses than the remaining neurons, whereas this response hierarchy was abolished under bimodal stimulation. \textcolor{blue}{Collectively, our findings demonstrate that V1 dynamically balances local modular specialization and global integration through context-dependent topological reconfiguration: unimodal processing is supported by hub-centric control, while cross-modal input drives a transition toward globally optimized, distributed architectures via increased connectivity efficiency. This work provides a novel network-level framework for understanding the mechanisms of multisensory integration, offering theoretical insights that advance our understanding of sensory information processing and inform future clinical applications targeting cross-modal neural plasticity.
Keywords: multimodal integration, functional network, graph theory, two-photon imaging, calcium imaging
Received: 01 Aug 2025; Accepted: 18 Sep 2025.
Copyright: © 2025 Li, Peng, He, Zhu, Li and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ming Li, liming78@nudt.edu.cn
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