ORIGINAL RESEARCH article
Front. Neural Circuits
Volume 19 - 2025 | doi: 10.3389/fncir.2025.1569158
This article is part of the Research TopicNeuro-inspired computationView all 6 articles
Vagus nerve stimulation modulates information representation of sustained activity in layer specific manner in the rat auditory cortex
Provisionally accepted
- 1Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo, Japan
- 2Department of Neurosurgery, Jichi Medical University, Tochigi, Tochigi, Japan
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Understanding how vagus nerve stimulation (VNS) modulates cortical information processing is essential to developing sustainable, adaptive artificial intelligence inspired by biological systems. This study presents the first evidence that VNS alters the representation of auditory information in a manner that is both layer-and frequency band-specific within the rat auditory cortex. Using a microelectrode array, we meticulously mapped the band-specific power and phase-locking value of sustained activities in layers 2/3, 4 and 5/6, of the rat auditory cortex. We used sparse logistic regression to decode the test frequency from these neural characteristics and compared the decoding accuracy before and after applying VNS. Our results showed that VNS impairs high-gamma band representation in deeper layers (layers 5/6), enhances theta band representation in those layers, and slightly improves high-gamma representation in superficial layers (layers 2/3 and 4), demonstrating the layer-specific and frequency band-specific effect of VNS. These findings suggest that VNS modulates the balance between feed-forward and feed-back pathways in the auditory cortex, providing novel insights into the mechanisms of neuromodulation and its potential applications in brain-inspired computing and therapeutic interventions.
Keywords: Vagus Nerve Stimulation, Auditory Cortex, sustained activity, Phase Locking Value, microelectrode array, machine learning, Sparse Logistic Regression
Received: 31 Jan 2025; Accepted: 07 Jul 2025.
Copyright: © 2025 Shiramatsu, Ibayashi, Kawai and Takahashi. 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: Hirokazu Takahashi, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo, Japan
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