Probabilistic optimization in the human perceptuo-motor system

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概要

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• Despite the variability of internal and external environments, the human central nervous system (CNS) can generate precise and stable perception and motor behaviors. What mechanism enables this ability? Answering this question is one of the significant goals in the human sciences, including neuroscience, cognitive science, physical education and sports science. The Bayesian integration theory proposes that the CNS learns the prior distribution of a task and integrates it with sensory information to minimize the effect of sensory noise. In this article, we introduce psychophysical reports using motor timing and temporal order judgment (TOJ) tasks that support the Bayesian integration theory. Subsequently, we demonstrate the event-related potentials (ERPs) behind Bayesian integration that operates in somatosensory TOJ.

• The Japanese Society of Physical Fitness and Sports Medicineの論文

著者

• Takeuchi Shigeki

  Sports Management Program, Faculty of Business and Information Sciences, Jobu University

• Sekiguchi Hirofumi

  Sports Management Program, Faculty of Business and Information Sciences, Jobu University

• Matsuzaki Kozue

  Research Institute of Kochi University of Technology

• Miyazaki Makoto

  Research Institute of Kochi University of Technology

関連論文

• Neural control of muscle lengthening: Task- and muscle-specificity
• Probabilistic optimization in the human perceptuo-motor system
• Probabilistic optimization in the human perceptuo-motor system

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