• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2016 Fiscal Year Final Research Report

Utilization of muscle fatigue to consolidate motor skill proficiency and the neurophysiology significance of muscle fatigue on cerebral cortex

Research Project

  • PDF
Project/Area Number 26282168
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypePartial Multi-year Fund
Section一般
Research Field Developmental mechanisms and the body works
Research InstitutionNiigata University of Health and Welfare

Principal Investigator

MARUYAMA ATSUO  新潟医療福祉大学, 健康科学部, 教授 (80117548)

Co-Investigator(Kenkyū-buntansha) 山代 幸哉  新潟医療福祉大学, 健康科学部, 講師 (20570782)
塗木 淳夫  鹿児島大学, 工学部, 准教授 (50336319)
佐藤 大輔  新潟医療福祉大学, 健康科学部, 講師 (60544393)
Co-Investigator(Renkei-kenkyūsha) HAMADA Masashi  東京大学, 医学部・歯学部附属病院, 助教 (40708054)
Project Period (FY) 2014-04-01 – 2017-03-31
Keywords筋疲労 / 運動野皮質内抑制低下 / 神経ネットワーク / 適応的運動学習 / 連続的運動学習 / 至適筋疲労 / 技術習熟神経強化
Outline of Final Research Achievements

We aimed to determine the effect of muscle fatigue on excitability level of each neural network between PMd, SMA, PPC and M1 connections and to quantify muscle fatigue levels to consolidate motor skill proficiency. We examined how muscle fatigue influences the neural network between them by TMS methods. Our results showed that muscle fatigue decreased the excitabilities of PMd- and SMA-M1 inhibitory connections and SICI in the motor cortex at the same time but did not change the excitability of PPC-M1 connection. We identified “optimal” muscle fatigue by showing the decreased SICI after some tasks of %MVC and contraction duration. We also examined whether the muscle fatigue could improve errors of muscle strength control in adaptive learning and typing speed in sequential learning. The results showed that muscle fatigue improved performance of both motor learning types. It is likely that optimal muscle fatigue consolidates motor skill proficiency in motor learning.

Free Research Field

複合領域

URL: 

Published: 2018-03-22  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi