PERSPECTIVE article
Front. Behav. Neurosci.
Sec. Emotion Regulation and Processing
Volume 19 - 2025 | doi: 10.3389/fnbeh.2025.1715460
This article is part of the Research TopicExploring CNS-ANS communication: Implications for mental and physical healthView all 6 articles
What can ANS signals tell us about motor learning? An implication for better assessment of cognitive contribution to motor learning
Provisionally accepted
- National Institute of Information and Communications Technology, Advanced ICT Research Institute Center for Information and Neural Networks, Suita, Japan
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Motor learning is supported by both explicit and implicit processes. A central question in the field of motor control is how these two processes interact and, critically, how each process can be assessed in an unbiased manner. In this perspective paper, we propose that the autonomic nervous system (ANS) offers an informative window into explicit cognitive processes during motor learning. We first briefly review studies outside the motor learning domain, where ANS activity has been linked to internal cognitive states such as surprise and uncertainty. We then discuss how these ANS-related states can be leveraged to assess the manifestation and influence of explicit processes during motor learning, as well as to explore cognitive computations that may involve central ANS activity, including contextual inference.
Keywords: Autonomic Nervous System, ANS, cognitive, motor learning, explicit, Implicit, Cognitive contribution, Contextual inference
Received: 29 Sep 2025; Accepted: 10 Oct 2025.
Copyright: © 2025 Yokoi. 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: Atsushi Yokoi, at.yokoi.work@gmail.com
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