Iwama, Seitaro

写真a

Affiliation

Faculty of Science and Technology, Department of Biosciences and Informatics (Yagami)

Position

Assistant Professor (Non-tenured)/Research Associate (Non-tenured)/Instructor (Non-tenured)

Related Websites
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Career 【 Display / hide 】

  • 2021.04
    -
    2023.03

    Japan Society for the Promotion of Science, 特別研究員（DC1）

  • 2021.08
    -
    2023.03

    Graduate School of Science and Technology, Keio University, Research Assistant

  • 2023.04
    -
    Present

    Keio University, Faculty of Science and Technology Department of Biosciences and Infomatics, Assistant Professor (Non-tenured)

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Academic Background 【 Display / hide 】

  • 2015.04
    -
    2019.03

    Keio University, Faculty of Science and Technology, Department of Biosciences and Infomatics

  • 2019.04
    -
    2020.09

    Keio University, Graduate School of Science and Technology, 基礎理工学専攻

  • 2020.09
    -
    2023.03

    Keio University, Graduate School of Science and Technology, 基礎理工学専攻

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Papers 【 Display / hide 】

  • Biofeedback training can enhance esports players’ shooting performance in an aiming task: focusing on cortical activity and gaze movement

    Inhyeok Jeong, Naotsugu Kaneko, Donghyun Kim, Ryogo Takahashi, Seitaro Iwama, Mayu Dohata, Junichi Ushiba, Kimitaka Nakazawa

    Computers in Human Behavior 175 2025.10

    ISSN  0747-5632

  • Enhanced human sensorimotor integration via self-modulation of the somatosensory activity

    Seitaro Iwama*, Takamasa Ueno*, Tatsuro Fujimaki, Junichi Ushiba, *: Equally contributed

    iScience (Elsevier BV)  28 ( 4 ) 112145 - 112145 2025.03

    Lead author, Corresponding author, Accepted,  ISSN  2589-0042

  • Improved motor imagery skills after repetitive passive somatosensory stimulation: a parallel-group, pre-registered study

    Kyoko Kusano, Masaaki Hayashi, Seitaro Iwama, Junichi Ushiba

    Frontiers in Neural Circuits (Frontiers Media SA)  18 2025.01

    Accepted

    　View Summary

    Introduction

    Motor-imagery-based Brain-Machine Interface (MI-BMI) has been established as an effective treatment for post-stroke hemiplegia. However, the need for long-term intervention can represent a significant burden on patients. Here, we demonstrate that motor imagery (MI) instructions for BMI training, when supplemented with somatosensory stimulation in addition to conventional verbal instructions, can help enhance MI capabilities of healthy participants.

    Methods

    Sixteen participants performed MI during scalp EEG signal acquisition before and after somatosensory stimulation to assess MI-induced cortical excitability, as measured using the event-related desynchronization (ERD) of the sensorimotor rhythm (SMR). The non-dominant left hand was subjected to neuromuscular electrical stimulation above the sensory threshold but below the motor threshold (St-NMES), along with passive movement stimulation using an exoskeleton. Participants were randomly divided into an intervention group, which received somatosensory stimulation, and a control group, which remained at rest without stimulation.

    Results

    The intervention group exhibited a significant increase in SMR-ERD compared to the control group, indicating that somatosensory stimulation contributed to improving MI ability.

    Discussion

    This study demonstrates that somatosensory stimulation, combining electrical and mechanical stimuli, can improve MI capability and enhance the excitability of the sensorimotor cortex in healthy individuals.

  • Neurofeedback-induced desynchronization of sensorimotor rhythm elicits pre-movement downregulation of intracortical inhibition that shortens simple reaction time in humans: a double-blind sham-controlled randomized study

    Yoshihito Muraoka, Seitaro Iwama, Junichi Ushiba

    Imaging Neuroscience (MIT Press)  Accepted 2024.10

    Accepted

    　View Summary

    Abstract

    Sensorimotor rhythm event-related desynchronization (SMR-ERD) is associated with the activities of cortical inhibitory circuits in the motor cortex. The self-regulation of SMR-ERD through neurofeedback training has demonstrated that successful SMR-ERD regulation improves motor performance. However, the training-induced changes in neural dynamics in the motor cortex underlying performance improvement remain unclear. Here, we hypothesized that SMR-neurofeedback based on motor imagery reduces cortical inhibitory activities during motor preparation, leading to shortened reaction time due to the repetitive recruitment of neural populations shared with motor imagery and movement preparation. To test this, we conducted a double-blind, sham-controlled study on twenty-four participants using neurofeedback training and pre- and post-training evaluation for simple reaction time tests and cortical inhibitory activity using short-interval intracortical inhibition (SICI). The results showed that veritable neurofeedback training effectively enhanced SMR-ERD in healthy male and female participants, accompanied by reduced simple reaction times and pre-movement SICI. Furthermore, SMR-ERD changes correlated with changes in pre-movement cortical disinhibition, and the disinhibition magnitude correlated with behavioral changes. These results suggest that SMR-neurofeedback modulates cortical inhibitory circuits during movement preparation, thereby enhancing motor performance.

  • EEG decoding with spatiotemporal convolutional neural network for visualization and closed‐loop control of sensorimotor activities: A simultaneous EEG‐fMRI study

    Seitaro Iwama, Shohei Tsuchimoto, Nobuaki Mizuguchi, Junichi Ushiba

    Human Brain Mapping (Wiley)  45 ( 9 )  2024.06

    Lead author, Accepted,  ISSN  1065-9471

    　View Summary

    Abstract

    Closed‐loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the associated behavioral performance. A spatiotemporal filter for high‐density whole‐head scalp EEG using a convolutional neural network can overcome the ambiguity of the signaling source because each EEG signal includes information on the remote regions. We simultaneously acquired EEG and functional magnetic resonance images in humans during the brain‐computer interface (BCI) based neurofeedback training and compared the reconstructed and modeled hemodynamic responses of the sensorimotor network. Filters constructed with a convolutional neural network captured activities in the targeted network with spatial precision and specificity superior to those of the EEG signals preprocessed with standard pipelines used in BCI‐based neurofeedback paradigms. The middle layers of the trained model were examined to characterize the neuronal oscillatory features that contributed to the reconstruction. Analysis of the layers for spatial convolution revealed the contribution of distributed cortical circuitries to reconstruction, including the frontoparietal and sensorimotor areas, and those of temporal convolution layers that successfully reconstructed the hemodynamic response function. Employing a spatiotemporal filter and leveraging the electrophysiological signatures of the sensorimotor excitability identified in our middle layer analysis would contribute to the development of a further effective neurofeedback intervention.

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Reviews, Commentaries, etc. 【 Display / hide 】

  • ブレイン・マシン・インターフェースからみた脳科学とリハビリテーション

    岩間清太朗， 牛場潤一

    理学療法-臨床・研究・教育 30 (1), 3-6 30 ( 1 ) 3 - 6 2023.09

    Lead author

  • Motor Learning and ʻObject-based Learningʼ ̶from the Perspective of Neuroscience̶ ̶

    Seitaro Iwama*, Masatoshi Kokubo*, Junichi Ushiba, (*: equally contributed)

    The KeMCO Review 1 2023.04

    Lead author

  • Brain-machine interface and neurorehabilitation

    Junichi Ushiba, Seitaro Iwama

    医学のあゆみ 275 ( 12, 13 ) 1240 - 1245 2020.12

  • Mechanisms, Evidences, and Meta-analysis in Brain-Machine Interface Based Motor Exercise

    Junichi Ushiba, Seitaro Iwama, Meigen Liu

    The Japanese Journal of Rehabilitation Medicine (Japanese Association of Rehabilitation Medicine)  57 ( 10 ) 956 - 964 2020.10

    ISSN  1881-3526

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • Elucidating the determinants of reaction time from the observation and manipulation of sensorimotor rhythms

    2024.04
    -
    2028.03

    Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), No Setting

  • パフォーマンスを安定化する脳状態の自己調節訓練法の確立

    2023.09
    -
    2027.03

    科学技術振興機構 ,  さきがけ 社会課題を解決する人間中心インタラクションの創出 , No Setting, Principal investigator

  • 次世代先端分野探索研究(新任者研究推進費)

    2023.06
    -
    2024.03

    慶應義塾先端科学技術研究センター, No Setting

  • 感覚運動ネットワークの再編成を誘導する標的定位型ニューロフィードバック法の開発

    2021.04
    -
    2024.03

    日本学術振興会, 科学研究費助成事業 特別研究員奨励費, 特別研究員奨励費, No Setting

    　View Summary

    本研究の目的は、運動関連脳領域の活動パタンから同定される感覚運動ネットワークを標的とした神経機能修飾技術の概念実証である。上肢運動機能に関連する脳内ネットワークの機能変化を誘導するニューロフィードバック法を開発するため、本年度は非侵襲な脳活動計測法である頭皮脳波から運動に関する情報のデコーディング技術について検討を進めた。
    半球間の位相同期性が感覚運動処理過程におけるひとつの介入焦点であることを、文献調査および今年度取得した健常成人30名のデータから見出した。また、補足運動野は従前の生理学研究から、運動計画の出力と両手運動の制御への関与が報告されている。この領域の興奮性と、接続する領域である一次運動野を一過的に調整し、その後に生じる行動課題パフォーマンスの変化を検討可能と着想した。
    そこで、不安定な両手運動の代表例である逆位相の両手運動に着目し、実験系の構築と予備検討を実施した。逆位相とは右手と左手で異なる指を動員することを指し、半球間の干渉により自発的に同じ指を動員する順位相へ転移する。ネットワークの再編成にともない、両手の独立性が向上するかを検証するため、行動学的に指の運動を記録するためのアクションカメラ映像、キーボードの入力タイミング記録を頭皮脳波計測下で行う実験系を構築した。指のタッピング運動に起因する体動を最小限にし、信号品質を担保するため、あごのせ台や体動に由来する信号を効果的に除去する独立成分分析を導入した。これにより、ハードウェアとソフトウェア、2つの観点から信号品質を改善するアプローチを実施したため、複数の被験者で安定的に行動課題中の頭皮脳波を計測し、脳波を実時間処理しフィードバックするシステムの構築が完了した。

  • Ushioda Memorial Fund (The Keio University Doctorate Student Grant-in-Aid Program)

    2021.04
    -
    2022.03

    Keio University, Principal investigator

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Awards 【 Display / hide 】

  • The Annual BCI Award 2024: Top 12 Nominees

    Taiga Seri, Seitaro Iwama, Kurumi Adachi, Junichi Ushiba, 2024, BCI Award Foundation, Intuitive avatar control through a non-invasive multimodal Brain-Computer Interface

  • The Japanese Society for Motor Control

    2022.08, Motor Control 研究会, Young Researcher Encouragement Award

  • MEXT

    2019.03, 文部科学省, Encouragement award at the 8th Science Intercollegiate

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Courses Taught 【 Display / hide 】

  • BASIC LABORATORY COURSE IN BIOSCIENCES

    2025

  • ADVANCED LABORATORY COURSE IN BIOSCIENCES AND INFORMATICS B

    2025

  • ADVANCED LABORATORY COURSE IN BIOSCIENCES AND INFORMATICS A

    2025

  • LABORATORY IN SCIENCE

    2025

  • TOPICS IN BIOSCIENCES AND INFORMATICS 2

    2025

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Courses Previously Taught 【 Display / hide 】

  • Mathematics for life sciences

    Keio University

    2023.09
    -
    Present

  • Comprehensive exercise for biosciences & informatics

    Keio University

    2023.09
    -
    Present

  • Laboratory in science

    Keio University

    2023.04
    -
    Present

  • Advanced laboratory course in biosciences and informatics

    Keio University

    2023.04
    -
    Present

  • Topics in biosciences and informatics

    Keio University

    2023.04
    -
    Present

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