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A unified model of unimanual and bimanual movements - theory, validation, and application

Research Project

Project/Area Number 16K16122
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Soft computing
Research InstitutionTokyo University of Agriculture and Technology

Principal Investigator

Takiyama Ken  東京農工大学, 工学(系)研究科(研究院), 特任准教授 (40725933)

Project Period (FY) 2016-04-01 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Keywords身体運動学習 / 運動プリミティブ / 片腕運動 / 両腕運動 / 神経回路網モデル / 身体運動制御 / 機械学習 / 運動学習 / 認知科学 / 知能機械 / 神経科学
Outline of Final Research Achievements

In our daily life, we manipulate our smartphones unimanually and tablet devices bimanually. Although unimanual and bimanual movements are familiar, the relation between those movements remains unclear. We investigated the relation based on computational modeling and behavioral experiments (in particular, motor adaptation experiments). Based on mathematical conditions to explain some previous behavioral results, it was possible to propose a novel mathematical model to explain the relation between unimanual and bimanual movements. We further validated the model based on behavioral experiments and the implementation of the model in a biologically plausible neural network model.

Report

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

    (28 results)

All 2018 2017 2016

All Journal Article (6 results) (of which Peer Reviewed: 6 results,  Open Access: 2 results,  Acknowledgement Compliant: 2 results) Presentation (22 results) (of which Int'l Joint Research: 9 results,  Invited: 12 results)

  • [Journal Article] Bayesian geodesic path for human motor control2017

    • Author(s)
      Ken Takiyama
    • Journal Title

      Neural networks

      Volume: 93 Pages: 137-142

    • DOI

      10.1016/j.neunet.2017.05.005

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network2017

    • Author(s)
      Ken Takiyama
    • Journal Title

      Journal of Physics A: Mathematical and Theoretical

      Volume: 50 Issue: 49 Pages: 4956011-13

    • DOI

      10.1088/1751-8121/aa91ae

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Detecting the relevance to performance of whole-body movements2017

    • Author(s)
      Daisuke Furuki, Ken Takiyama
    • Journal Title

      Sci Rep.

      Volume: 7 Issue: 1 Pages: 156591-14

    • DOI

      10.1038/s41598-017-15888-3

    • NAID

      130006189580

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] A balanced motor primitive framework can simultaneously explain motor learning in unimanual and bimanual movements2017

    • Author(s)
      Takiyama K, Sakai Y
    • Journal Title

      Neural Networks

      Volume: 86 Pages: 80-89

    • DOI

      10.1016/j.neunet.2016.10.013

    • Related Report
      2016 Research-status Report
    • Peer Reviewed / Open Access
  • [Journal Article] Optimal multiple-information integration inherent in a ring neural network2017

    • Author(s)
      Ken Takiyama
    • Journal Title

      Journal of Physics A: Mathematical and Theoretical

      Volume: 50 Issue: 8 Pages: 1-12

    • DOI

      10.1088/1751-8121/aa5577

    • Related Report
      2016 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] Maximization of learning speed due to neuronal redundancy in reinforcement learning2016

    • Author(s)
      Ken Takiyama
    • Journal Title

      Journal of Physical Society of Japan

      Volume: 85 Issue: 11 Pages: 1-6

    • DOI

      10.7566/jpsj.85.114801

    • NAID

      40020994936

    • Related Report
      2016 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] Prospective coding in motor learning and motor decision making2018

    • Author(s)
      Ken Takiyama
    • Organizer
      the 18th workshop of brain and mind
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Prospective coding in motor learning and motor decision making2018

    • Author(s)
      瀧山 健
    • Organizer
      脳科学ライフサポート研究センターセミナー
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] Detecting the relevance of each motion component in whole-body motion to performance2017

    • Author(s)
      Ken Takiyama, Daisuke Furuki
    • Organizer
      the XXVI Congress of the International Society of Biomechanics (ISB)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Influence of switching rule on motor learning2017

    • Author(s)
      Ken Takiyama, Koutaro Ishii, Takuji Hayashi
    • Organizer
      Annual meeting of Society for Neuroscience (SfN2017)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Competitive game influences risk-sensitivity in motor decision-making2017

    • Author(s)
      Keiji Ota, Takuji Hayashi, Ken Takiyama
    • Organizer
      Annual meeting of Society for Neuroscience (SfN2017)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Motor learning rate is influenced by prior motor learning through reconfiguration of directional preference of motor primitives2017

    • Author(s)
      Takuji Hayashi, Ken Takiyama, Daichi Nozaki
    • Organizer
      Annual meeting of Society for Neuroscience (SfN2017)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Application of POrtable Motor learning LABoratory (PoMLab): cross-syndrome comparison of implicit visuomotor adaptation among patients with stroke and Parkinson’ s disease2017

    • Author(s)
      Masahiro Shinya, Ken Takiyama, Takeshi Sakurada, Shin-ichi Muramatsu, Hirofumi Ogihara, Takaaki Sato, Taiki Komatsu
    • Organizer
      Annual meeting of Society for Neuroscience (SfN2017)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] パフォーマンスに関連した運動要素の同定2017

    • Author(s)
      瀧山 健
    • Organizer
      日本機械学会 シンポジウム: スポーツ工学・ヒューマンダイナミクス
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] 運動学習の統一理論モデル -誤差の予測の重要性-2017

    • Author(s)
      瀧山健, 平島雅也, 野崎大地
    • Organizer
      数理生物学会
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] ルールの切り替えが運動学習に及ぼす影響2017

    • Author(s)
      瀧山健, 石井恒太郎, 林拓司
    • Organizer
      日本神経回路学会
    • Related Report
      2017 Annual Research Report
  • [Presentation] パフォーマンスに関連する・関連しない運動要素の同定2017

    • Author(s)
      瀧山健
    • Organizer
      スポーツ科学セミナー
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] 競争課題は運動意思決定におけるリスク感受性に影響する2017

    • Author(s)
      太田啓示, 瀧山健
    • Organizer
      体力医学会
    • Related Report
      2017 Annual Research Report
  • [Presentation] 自分の運動学習能力を測ってみよう2017

    • Author(s)
      瀧山健
    • Organizer
      創発シンポジウム
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] ルールの切り替えが運動学習に及ぼす影響2017

    • Author(s)
      瀧山健, 石井恒太郎, 林拓司
    • Organizer
      Motor Control 研究会
    • Related Report
      2017 Annual Research Report
  • [Presentation] Influence of switching rule on motor learning2017

    • Author(s)
      Ken Takiyama, Kohtaro Ishii, Takuji Hayashi
    • Organizer
      日本神経科学学会
    • Related Report
      2017 Annual Research Report
  • [Presentation] 全身運動におけるパフォーマンスへの関連度の同定2017

    • Author(s)
      瀧山健, 古木大祐
    • Organizer
      第61回システム制御情報学会研究発表講演会 (SCI’17)
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] 運動学習の統一理論モデル -誤差の予測の重要性-2017

    • Author(s)
      瀧山健
    • Organizer
      電子情報通信学会 東海支部 第3回学生会講演会
    • Place of Presentation
      中部大学 (愛知県春日井市)
    • Related Report
      2016 Research-status Report
    • Invited
  • [Presentation] Prospective errors determine motor learning - a step towards a unified model of motor learning -2016

    • Author(s)
      Ken Takiyama
    • Organizer
      Modeling Neural Activity (MONA2)
    • Place of Presentation
      Waikoloa Beach Mrriott, Hawaii, United state
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Prospective errors determine motor learning - a step towards a unified model of motor learning -2016

    • Author(s)
      Ken Takiyama
    • Organizer
      Neurolunch
    • Place of Presentation
      Harvard University, Boston, United state
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Portable Motor Learning Laboratory (PoMLab)2016

    • Author(s)
      Shinya Masahiro, Ken Takiyama
    • Organizer
      Annual meeting of Society for Neuroscience (SfN2016)
    • Place of Presentation
      Convention center, San Diego, United states
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Presentation] 運動学習の統一理論モデル -誤差の予測の重要性-2016

    • Author(s)
      瀧山健
    • Organizer
      第10回 Motor Control 研究会
    • Place of Presentation
      慶応大学 (神奈川県日吉市)
    • Related Report
      2016 Research-status Report
    • Invited
  • [Presentation] 運動学習の統一理論モデル -誤差の予測の重要性-2016

    • Author(s)
      瀧山健
    • Organizer
      計測自動制御学会ライフエンジニアリング部門シンポジウム
    • Place of Presentation
      大阪国際交流センター (大阪府大阪市)
    • Related Report
      2016 Research-status Report
    • Invited

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Published: 2016-04-21   Modified: 2019-03-29  

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