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A study of neural plasticity mechanisms behind brain-machine interface control and learning

Research Project

Project/Area Number 16K01469
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Rehabilitation science/Welfare engineering
Research InstitutionKeio University

Principal Investigator

Ushiba Junichi  慶應義塾大学, 理工学部(矢上), 准教授 (00383985)

Project Period (FY) 2016-04-01 – 2019-03-31
Project Status Completed (Fiscal Year 2018)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2016: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Keywordsブレイン・マシン・インターフェース / 可塑性 / 運動学習 / 頭皮脳波 / リハビリテーション / 神経リハビリテーション / fMRI-EEG同時計測 / 誤差学習
Outline of Final Research Achievements

As the number of EEG-BMI trials was increased, the initial EEG response prior to the onset of BMI control, an analogue of motor-related cortical potentials, was gradually increased. The data suggests feedforward model of BCI control was maturated in a trial by trial manner. In parallel to such skill acquisition process, the researcher further explored alternative learning/plasticity process using f-MRI. The parietal-temporal regions were identified to determine successful BMI control, suggesting visuomotor adaptation/computation is a considerable key to facilitate BMI use. The subcortical reward systems were not activated in the current BMI setting. Gamified BMI may promote reward-based reinforcement learning. Finally, the researcher tested what parameters of neuromuscular electrical stimulation actuates peripheral sensory nerves to send facilitatory signals to the cortex. The study revealed that wide pulse, high frequency stimulation activated thalamus and sensorimotor cortex.

Academic Significance and Societal Importance of the Research Achievements

傷害を受け、病態が慢性化した脳にも、情報伝達効率や機能特性を変容させる可塑性能力があり、BMIリハによってそれを引き出すことができると現在は考えられている。しかし、BMIリハのどの要素が、脳のどこに働きかけ、どういったルールに基づいて何を変化させているのか、詳しいメカニズムは不明であった。メカニズムの理解なしには、「傷害脳の特性に応じた治療手技の改良」や「適用基準と併用禁忌の判定」が理論的におこなわれず、科学性に基づく医療の確立と今後のBMI研究の着実な発展が望めない。本研究によってメカニズムの一端が明らかになったことは、BMIの科学的発展や健全な医療応用を促す上で大きな意義がある。

Report

(4 results)
  • 2018 Annual Research Report   Final Research Report ( PDF )
  • 2017 Research-status Report
  • 2016 Research-status Report
  • Research Products

    (2 results)

All 2018 2016

All Presentation (2 results) (of which Int'l Joint Research: 2 results)

  • [Presentation] EEG-based brain-computer interface using deep neural network for point by point decoding: A pilot study2018

    • Author(s)
      Yosuke Fujiwara, Satoshi Honda, Junichi Ushiba
    • Organizer
      Neuroscience 2018
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Cortical current source estimation improves detection of sensorimotor rhythm in resting-state: Validation through simultaneous EEG-fMRI recording in humans2016

    • Author(s)
      S. SHIBUSAWA, S. TSUCHIMOTO, S. KASUGA, K. KATO, E. YAMADA, H. EBATA, M. LIU, J. USHIBA
    • Organizer
      Neuroscience 2016 (SfN)
    • Place of Presentation
      サンディエゴ、米国
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research

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Published: 2016-04-21   Modified: 2021-01-27  

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