研究者データベース
瀧山 健TAKIYAMA Kenタキヤマ ケン
| ■所属部署名 | 工学研究院 先端電気電子部門 | |||
| ■職名 | 准教授 | |||
Last Updated :2025/07/18
業績情報
氏名・連絡先
氏名
タキヤマ ケン, 瀧山 健, TAKIYAMA Ken
主たる所属・職名
工学研究院 先端電気電子部門, 准教授
その他の所属
教育・研究活動状況
科学研究費助成事業
- 基盤研究（C）
「ばらつき」に基づくスポーツパフォーマンス評価手法の再構築
自 2024年, 至 2024年 - 基盤研究(B)
身体運動制御・身体運動学習の協調関係ならびに神経基盤の包括的理解とその応用
自 2024年, 至 2026年 - 国際共同研究加速基金（国際共同研究強化(B)）
技能の熟達と喪失に関わる感覚運動機能の神経可塑性の包括的理解
自 2022年, 至 2022年 - 国際共同研究加速基金（国際共同研究強化(B)）
技能の熟達と喪失に関わる感覚運動機能の神経可塑性の包括的理解
自 2021年, 至 2021年 - 基盤研究(B)
身体運動学習-身体運動制御の統一理論の構築・実証とその応用
自 2020年, 至 2024年 - 国際共同研究加速基金（国際共同研究強化(B)）
技能の熟達と喪失に関わる感覚運動機能の神経可塑性の包括的理解
自 2020年, 至 2020年 - 国際共同研究加速基金（国際共同研究強化(B)）
技能の熟達と喪失に関わる感覚運動機能の神経可塑性の包括的理解
自 2019年, 至 2019年 - 若手研究
運動学習-運動制御の統一的枠組みに基づく運動学習の統一モデル構築
自 2018年, 至 2019年 - 挑戦的萌芽研究
テイラーメイドトレーニングのための運動学習パラメータ測定プラットフォームの開発
自 2018年, 至 2018年 - 挑戦的萌芽研究
テイラーメイドトレーニングのための運動学習パラメータ測定プラットフォームの開発
自 2017年, 至 2017年 - 若手研究(B)
片腕運動-両腕運動の運動学習統一理論モデルの構築、実証とその応用
自 2016年, 至 2017年 - 挑戦的萌芽研究
テイラーメイドトレーニングのための運動学習パラメータ測定プラットフォームの開発
自 2016年, 至 2016年
論文
- Speed-dependent modulations of muscle modules in the gait of people with radiographical and asymptomatic knee osteoarthritis and elderly controls: Case-control pilot study
Takiyama, Ken; Kubota, Keisuke; Yokoyama, Hikaru; Kanemura, Naohiko
JOURNAL OF BIOMECHANICS
ELSEVIER SCI LTD
This study investigates the muscle modules involved in the increase of walking speed in radiographical and asymptomatic knee osteoarthritis (KOA) patients using tensor decomposition. The human body possesses redundancy, which is the property to achieve desired movements with more degrees of freedom than necessary. The muscle module hypothesis is a proposed solution to this redundancy. While previous studies have examined the pathological muscle activity modulations in musculoskeletal diseases such as KOA, they have focused on single muscles rather than muscle modules. Moreover, most studies have only examined the gait of KOA patients at a single speed, leaving the way in which gait speed affects gait parameters in KOA patients unclear. Assessing this influence is crucial for determining appropriate gait speed and understanding why preferred gait speed decreases in KOA patients. In this study, we apply tensor decomposition to muscle activity data to extract muscle modules in KOA patients and elderly controls during walking at different speeds. We found a muscle module comprising hip adductors and back muscles that activate bimodally in a gait cycle, specific to KOA patients when they increase their walking speed. These findings may provide valuable insights for rehabilitation for KOA patients.
2024年06月, 研究論文（学術雑誌）, 共同, 171, 0021-9290, DOI(公開)(r-map) - Guidelines for balancing the number of trials and the number of subjects to ensure the statistical power to detect variability - Implication for gait studies
Shinya, Masahiro; Takiyama, Ken
JOURNAL OF BIOMECHANICS
ELSEVIER SCI LTD
Variability is one of the most crucial outcomes in human movement studies: variance and standard deviation of various parameters have been reported in numerous studies. However, in many of these studies, the numbers of trials and subjects have been intuitively determined and not justified with statistical considerations. Here, we investigated the impact of the numbers of trials and subjects on statistical power, based on the assumption that results per trial follow a normal distribution, using mathematical analysis and numerical simulation. An inverselike relationship was observed between the number of trials and subjects required to ensure the statistical power for detecting differences in variance between subject groups or conditions. For instance, assuming a 1.2-times difference in population variance between pre-and post-training sessions as an alternative hypothesis, our simulation demonstrated that combinations of the number of subjects and trials, such as measuring 100 trials from each of 12 subjects under each condition, or measuring 20 trials from each of 60 subjects, can guarantee an 80 % of statistical power. Planning research based on such mathematical considerations will enable meaningful statistical interpretations in studies focusing on movement variability, such as gait studies.
2024年03月, 研究論文（学術雑誌）, 共同, 165, 0021-9290, DOI(公開)(r-map) - Speed-dependent modulations of asymmetric center of body mass trajectory in the gait of above-knee amputee subjects
Takiyama, Ken; Yokoyama, Hikaru
FRONTIERS IN SPORTS AND ACTIVE LIVING
FRONTIERS MEDIA SA
2024年01月04日, 研究論文（学術雑誌）, 共同, 5, DOI(公開)(r-map) - Transition between individually different and common features in skilled drumming movements.
Ken Takiyama, Masaya Hirashima, Shinya Fujii
Frontiers in Sports and Active Living
2023年06月26日, 研究論文（学術雑誌）, 共同, 4:923180, DOI(公開)(r-map), 1, 14 - Detecting task-relevant spatiotemporal modules and their relation to motor adaptation.
Masato Inoue, Daisuke Furuki, Ken Takiyama
PLOS ONE
PUBLIC LIBRARY SCIENCE
How does the central nervous system (CNS) control our bodies, including hundreds of degrees of freedom (DoFs)? A hypothesis to reduce the number of DoFs posits that the CNS controls groups of joints or muscles (i.e., modules) rather than each joint or muscle independently. Another hypothesis posits that the CNS primarily controls motion components relevant to task achievements (i.e., task-relevant components). Although the two hypotheses are examined intensively, the relationship between the two concepts remains unknown, e.g., unimportant modules may possess task-relevant information. Here, we propose a framework of task-relevant modules, i.e., modules relevant to task achievements, while combining the two concepts mentioned above in a data-driven manner. To examine the possible role of the task-relevant modules, we examined the modulation of the task-relevant modules in a motor adaptation paradigm in which trial-to-trial modifications of motor output are observable. The task-relevant modules, rather than conventional modules, showed adaptation-dependent modulations, indicating the relevance of task-relevant modules to trial-to-trial updates of motor output. Our method provides insight into motor control and adaptation via an integrated framework of modules and task-relevant components.
2022年10月07日, 研究論文（学術雑誌）, 共同, 17, 10, DOI(公開)(r-map) - Impaired feedforward control of movements in pianists with focal dystonia
Takiyama, Ken; Mugikura, Shuta; Furuya, Shinichi
FRONTIERS IN NEUROLOGY
FRONTIERS MEDIA SA
Learning accurate and fast movements typically accompanies the modulation of feedforward control. Nevertheless, it remains unclear how motor skill learning modulates feedforward control, such as through maladaptation of the sensorimotor system by extensive training (e.g., task-specific dystonia). Here, we examined the modulation of feedforward control through motor skill learning while focusing on the motion of piano playing at either a natural tempo or the fastest tempo. The current study compared the kinematics and keypress data among individuals in three groups: healthy and well-trained pianists (i.e., subjects with skill learning), non-musicians (i.e., subjects without skill learning), and patients with focal-hand dystonia (FHD) (i.e., subjects with maladaptation by skill learning). Compared to healthy pianists, patients with FHD showed impairment in some feedforward motion components that are relevant to classifying the two playing tempi. However, while focusing on motion components that are irrelevant to the tempo classification, patients with FHD showed movements comparable to those of healthy pianists. Furthermore, patients with FHD demonstrated significantly slower movement times than healthy pianists. Our results suggest that maladaptation by skill learning affects parts of feedforward control rather than its entirety. Nevertheless, the affected feedforward components are relevant to performing movements as fast as possible, which may underlie the speed dependence of dystonic symptoms.
2022年08月12日, 研究論文（学術雑誌）, 共同, 13, 1664-2295, DOI(公開)(r-map) - Effort-dependent effects on uniform and diverse muscle activity features in skilled pitching
Hashimoto, Tsubasa; Takiyama, Ken; Miki, Takeshi; Kobayashi, Hirofumi; Nasu, Daiki; Ijiri, Tetsuya; Kuwata, Masumi; Kashino, Makio; Nakazawa, Kimitaka
SCIENTIFIC REPORTS
NATURE PORTFOLIO
How do skilled players change their motion patterns depending on motion effort? Pitchers commonly accelerate wrist and elbow joint rotations via proximal joint motions. Contrastingly, they show individually different pitching motions, such as in wind-up or follow-through. Despite the generality of the uniform and diverse features, effort-dependent effects on these features are unclear. Here, we reveal the effort dependence based on muscle activity data in natural three-dimensional pitching performed by skilled players. We extract motor modules and their effort dependence from the muscle activity data via tensor decomposition. Then, we reveal the unknown relations among motor modules, common features, unique features, and effort dependence. The current study clarifies that common features are obvious in distinguishing between low and high effort and that unique features are evident in differentiating high and highest efforts.
2021年04月15日, 研究論文（学術雑誌）, 共同, 11, 1, 2045-2322, DOI(公開)(r-map) - Competition Rather Than Observation and Cooperation Facilitates Optimal Motor Planning
Mamoru Tanae†, Keiji Ota†*, Ken Takiyama* († ... equally contributed, * ... correspondence)
Frontiers in Sports and Active Living
2021年02月26日, 研究論文（学術雑誌）, 共同, DOI(公開)(r-map) - Speed- and mode-dependent modulation of the center of mass trajectory in human gaits as revealed by Lissajous curves
Takiyama, Ken; Yokoyama, Hikaru; Kaneko, Naotsugu; Nakazawa, Kimitaka
JOURNAL OF BIOMECHANICS
ELSEVIER SCI LTD
The central nervous system (CNS) achieves a stable gait at several speeds and modes while controlling diverse instability. An essential feature of a gait is the motion of the center of body mass (CoM). CoM motion is at larger risk for trespassing the base of support in the mediolateral direction than in the anteroposterior direction. How the CoM trajectory in the frontal plane changes depending on the speed or mode can thus provide insights about the neural control of stable gaits. Here, we reveal the speedand mode-dependent modulations of the trajectory by utilizing a Lissajous curve. The current study clarifies that speed-dependent modulations are evident in walking. Between walking and running, there were significant mode-dependent modulations. In contrast, there were no significant speed-dependent modulations during running. Deviations from standard tendencies quantified via Lissajous curve fitting could be a sign of gait impairments and recovery after treatments. (C) 2020 Elsevier Ltd. All rights reserved.
2020年09月18日, 研究論文（学術雑誌）, 共同, 110, 0021-9290, DOI(公開)(r-map) - Larger, but not better, motor adaptation ability inherent in medicated Parkinson's disease patients revealed by a smart-device-based study
Takiyama, Ken; Sakurada, Takeshi; Shinya, Masahiro; Sato, Takaaki; Ogihara, Hirofumi; Komatsu, Taiki
SCIENTIFIC REPORTS
NATURE PUBLISHING GROUP
Generating appropriate motor commands is an essential brain function. To achieve proper motor control in diverse situations, predicting future states of the environment and body and modifying the prediction are indispensable. The internal model is a promising hypothesis about brain function for generating and modifying the prediction. Although several findings support the involvement of the cerebellum in the internal model, recent results support the influence of other related brain regions on the internal model. A representative example is the motor adaptation ability in Parkinson's disease (PD) patients. Although this ability provides some hints about how dopamine deficits and other PD symptoms affect the internal model, previous findings are inconsistent; some reported a deficit in the motor adaptation ability in PD patients, but others reported that the motor adaptation ability of PD patients is comparable to that of healthy controls. A possible factor causing this inconsistency is the difference in task settings, resulting in different cognitive strategies in each study. Here, we demonstrate a larger, but not better, motor adaptation ability in PD patients than in healthy controls while reducing the involvement of cognitive strategies and concentrating on implicit motor adaptation abilities. This study utilizes a smart-device-based experiment that enables motor adaptation experiments anytime and anywhere with less cognitive strategy involvement. The PD patients showed a significant response to insensible environmental changes, but the response was not necessarily suitable for adapting to the changes. Our findings support compensatory cerebellar functions in PD patients from the perspective of motor adaptation.
2020年04月28日, 研究論文（学術雑誌）, 共同, 10, 1, 2045-2322, DOI(公開)(r-map) - A data-driven approach to decompose motion data into task-relevant and task-irrelevant components in categorical outcome
Furuki, Daisuke; Takiyama, Ken
SCIENTIFIC REPORTS
NATURE PUBLISHING GROUP
Decomposition of motion data into task-relevant and task-irrelevant components is an effective way to clarify the diverse features involved in motor control and learning. Several previous methods have succeeded in this type of decomposition while focusing on the clear relation of motion to both a specific goal and a continuous outcome, such as a 10 mm deviation from a target or 1 m/s hand velocity. In daily life, it is vital to quantify not only continuous but also categorical outcomes. For example, in baseball, batters must judge whether the opposing pitcher will throw a fastball or a breaking ball; tennis players must decide whether an opposing player will serve out wide or down the middle. However, few methods have focused on quantifying categorical outcome; thus, how to decompose motion data into task-relevant and task-irrelevant components when the outcome is categorical rather than continuous remains unclear. Here, we propose a data-driven method to decompose motion data into task-relevant and task-irrelevant components when the outcome takes categorical values. We applied our method to experimental data where subjects were required to throw fastballs or breaking balls with a similar form. Our data-driven approach can be applied to the unclear relation between motion and outcome, and the relation can be estimated in a data-driven manner. Furthermore, our method can successfully evaluate how the task-relevant components are modulated depending on the task requirements.
2020年02月12日, 研究論文（学術雑誌）, 共同, 10, 1, 2045-2322, DOI(公開)(r-map) - Optimizing motor decision-making through competition with opponents
Ota, Keiji; Tanae, Mamoru; Ishii, Kotaro; Takiyama, Ken
SCIENTIFIC REPORTS
NATURE PUBLISHING GROUP
Although optimal decision-making is essential for sports performance and fine motor control, it has been repeatedly confirmed that humans show a strong risk-seeking bias, selecting a risky strategy over an optimal solution. Despite such evidence, the ideal method to promote optimal decision-making remains unclear. Here, we propose that interactions with other people can influence motor decision-making and improve risk-seeking bias. We developed a competitive reaching game (a variant of the chicken game) in which aiming for greater rewards increased the risk of no reward and subjects competed for the total reward with their opponent. The game resembles situations in sports, such as a penalty kick in soccer, service in tennis, the strike zone in baseball, or take-off in ski jumping. In five different experiments, we demonstrated that, at the beginning of the competitive game, the subjects robustly switched their risk-seeking strategy to a risk-averse strategy. Following the reversal of the strategy, the subjects achieved optimal decision-making when competing with risk-averse opponents. This optimality was achieved by a non-linear influence of an opponent's decisions on a subject's decisions. These results suggest that interactions with others can alter human motor decision strategies and that competition with a risk-averse opponent is key for optimizing motor decision-making.
2020年01月22日, 研究論文（学術雑誌）, 共同, 10, 1, 2045-2322, DOI(公開)(r-map) - Speed-dependent and mode-dependent modulations of spatiotemporal modules in human locomotion extracted via tensor decomposition
Takiyama, Ken; Yokoyama, Hikaru; Kaneko, Naotsugu; Nakazawa, Kimitaka
SCIENTIFIC REPORTS
NATURE PUBLISHING GROUP
How the central nervous system (CNS) controls many joints and muscles is a fundamental question in motor neuroscience and related research areas. An attractive hypothesis is the module hypothesis: the CNS controls groups of joints or muscles (i.e., spatial modules) by providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. Another fundamental question is how the CNS generates numerous repertoires of movement patterns. One hypothesis is that the CNS modulates the spatial and/or temporal modules depending on the required tasks. It is thus essential to quantify the spatial modules, the temporal modules, and the task-dependent modulation of these modules. Although previous attempts at such quantification have been made, they considered modulation either only in spatial modules or only in temporal modules. These limitations may be attributable to the constraints inherent to conventional methods for quantifying the spatial and temporal modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the spatial modules, the temporal modules, and the task-dependent modulation of these modules without such limitations. We further demonstrate that tensor decomposition offers a new perspective on the task-dependent modulation of spatiotemporal modules: in switching from walking to running, the CNS modulates the peak timing in the temporal modules while recruiting more proximal muscles in the corresponding spatial modules.
2020年01月20日, 研究論文（学術雑誌）, 共同, 10, 1, 2045-2322, DOI(公開)(r-map) - Decomposing motion that changes over time into task-relevant and task-irrelevant components in a data-driven manner: application to motor adaptation in whole-body movements
Daisuke Furuki, Ken Takiyama
Scientific Reports
2019年05月10日, 研究論文（学術雑誌）, 共同, DOI(公開)(r-map) - Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network
Takiyama, Ken
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
IOP PUBLISHING LTD
How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.
2017年12月, 研究論文（学術雑誌）, 単独, 50, 49, 1751-8113, DOI(公開)(r-map) - Detecting the relevance to performance of whole-body movements
Furuki, Daisuke; Takiyama, Ken
SCIENTIFIC REPORTS
NATURE PUBLISHING GROUP
Goal-directed whole-body movements are fundamental in our daily life, sports, music, art, and other activities. Goal-directed movements have been intensively investigated by focusing on simplified movements (e.g., arm-reaching movements or eye movements); however, the nature of goal-directed whole-body movements has not been sufficiently investigated because of the high-dimensional nonlinear dynamics and redundancy inherent in whole-body motion. One open question is how to overcome high-dimensional nonlinear dynamics and redundancy to achieve the desired performance. It is possible to approach the question by quantifying how the motions of each body part at each time point contribute to movement performance. Nevertheless, it is difficult to identify an explicit relation between each motion element (the motion of each body part at each time point) and performance as a result of the high-dimensional nonlinear dynamics and redundancy inherent in whole-body motion. The current study proposes a data-driven approach to quantify the relevance of each motion element to the performance. The current findings indicate that linear regression may be used to quantify this relevance without considering the high-dimensional nonlinear dynamics of whole-body motion.
2017年11月, 研究論文（学術雑誌）, 共同, 7, 2045-2322, DOI(公開)(r-map) - Bayesian geodesic path for human motor control
Takiyama, Ken
NEURAL NETWORKS
PERGAMON-ELSEVIER SCIENCE LTD
Despite a near-infinite number of possible movement trajectories, our body movements exhibit certain invariant features across individuals; for example, when grasping a cup, individuals choose an approximately linear path from the hand to the cup. Based on these experimental findings, many researchers have proposed optimization frameworks to determine desired movement trajectories. Successful conventional frameworks include the geodesic path, which considers the geometry of our complicated body dynamics, and stochastic frameworks, which consider movement variability. The former succeed in explaining the kinematics in human reaching movements, and the latter succeed in explaining the variability in those movements. However, the conventional geodesic path framework does not consider variability, and the conventional stochastic frameworks do not consider the geometrical properties of our bodies. Thus, how to reconcile these two successful frameworks remains unclear. Here, I show that the conventional geodesic path can be interpreted as a Bayesian framework in which no uncertainty is considered. Hence, by introducing uncertainty into the framework, I propose a Bayesian geodesic path framework that can simultaneously consider the geometric properties of our bodies and movement variability. I demonstrate that the Bayesian geodesic path generates a mean movement trajectory that corresponds to the conventional geodesic path and a variability of movement trajectory, thus explaining the characteristic variability in human reaching movements. (C) 2017 Elsevier Ltd. All rights reserved.
2017年09月, 研究論文（学術雑誌）, 単独, 93, 0893-6080, DOI(公開)(r-map), 137, 142 - Optimal multiple-information integration inherent in a ring neural network
Takiyama, Ken
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
IOP PUBLISHING LTD
Although several behavioral experiments have suggested that our neural system integrates multiple sources of information based on the certainty of each type of information in the manner of maximum-likelihood estimation, it is unclear how the maximum-likelihood estimation is implemented in our neural system. Here, I investigate the relationship between maximum-likelihood estimation and a widely used ring-type neural network model that is used as a model of visual, motor, or prefrontal cortices. Without any approximation or ansatz, I analytically demonstrate that the equilibrium of an order parameter in the neural network model exactly corresponds to the maximum-likelihood estimation when the strength of the symmetrical recurrent synaptic connectivity within a neural population is appropriately stronger than that of asymmetrical connectivity, that of local and external inputs, and that of symmetrical or asymmetrical connectivity between different neural populations. In this case, strengths of local and external inputs or those of symmetrical connectivity between different neural populations exactly correspond to the input certainty in maximum-likelihood estimation. Thus, my analysis suggests appropriately strong symmetrical recurrent connectivity as a possible candidate for implementing the maximum-likelihood estimation within our neural system.
2017年02月, 研究論文（学術雑誌）, 単独, 50, 8, 1751-8113, DOI(公開)(r-map) - A balanced motor primitive framework can simultaneously explain motor learning in unimanual and bimanual movements
Takiyama, Ken; Sakai, Yutaka
NEURAL NETWORKS
PERGAMON-ELSEVIER SCIENCE LTD
Certain theoretical frameworks have successfully explained motor learning in either unimanual or bimanual movements. However, no single theoretical framework can comprehensively explain motor learning in both types of movement because the relationship between these two types of movement remains unclear. Although our recent model of a balanced motor primitive framework attempted to simultaneously explain motor learning in unimanual and bimanual movements, this model focused only on a limited subset of bimanual movements and therefore did not elucidate the relationships between unimanual movements and various bimanual movements. Here, we extend the balanced motor primitive framework to simultaneously explain motor learning in unimanual and various bimanual movements as well as the transfer of learning effects between unimanual and various bimanual movements; these phenomena can be simultaneously explained if the mean activity of each primitive for various unimanual movements is balanced with the corresponding mean activity for various bimanual movements. Using this balanced condition, we can reproduce the results of prior behavioral and neurophysiological experiments. Furthermore, we demonstrate that the balanced condition can be implemented in a simple neural network model. (C) 2016 The Author(s). Published by Elsevier Ltd.
2017年02月, 研究論文（学術雑誌）, 共同, 86, 0893-6080, DOI(公開)(r-map), 80, 89
著書
研究発表、招待講演等
- 身体運動に内在する低次元空間成分とその課題依存的変調
日本電気生理運動学会 (JSEK)
2023年03月11日, 口頭発表（招待・特別） - 運動学習への理論-データ駆動型アプローチ
MC研究会冬季講習
2021年01月09日, 口頭発表（招待・特別） - 身体運動データに潜む課題関連成分を抽出する (SARS-CoV-2の感染拡大により休止)
2020年03月20日, 口頭発表（招待・特別） - 既存理論の鳥瞰図を描く -身体運動制御・身体運動学習の統一的枠組みを目指して-
2019年11月10日, 口頭発表（招待・特別） - Detecting task-dependent modulation and individual difference of spatiotemporal module via tensor decomposition
2019年09月16日, 口頭発表（招待・特別） - How to reveal neural mechanisms of motor learning from human behavior?
2019年07月, 口頭発表（招待・特別）
委員歴
- 日本神経回路学会
出版理事
自 202204, 至 202403 - Motor Control 研究会
学術委員、ホームページ委員
自 20210401, 至 20230331 - Motor Control 研究会
アウトリーチ委員会
自 20190401, 至 20210331 - IEEE Computational Intelligence Society in Japan
幹事補佐
自 20190401, 至 20210331
メディア報道
- 格下との対戦で最適な運動パフォーマンス、東京農工大学が発見
スポーツで弱い相手と対戦することで運動パフォーマンスを高められることを、東京農工大学大学院工学研究院の瀧山健准教授、太田啓志研究員らの研究チームが突き止めたことが紹介される。
大学ジャーナル
自 2020年02月04日, 至 2020年02月04日 - 弱い相手と対戦すれば最適な運動戦略へと導かれる 東京農工大の研究
東京農工大学は1月27日、弱い相手との対戦が個々の運動能力に対して最適な運動戦略へと導かれることを明らかにしたと発表したことが紹介される。
財経新聞／Biglobeニュース／Livedoorニュース
自 2020年02月01日, 至 2020年02月01日 - データから動作の学習を考える ── 運動学習を見極める研究
月刊トレーニングジャーナル
自 2019年08月01日, 至 2019年08月01日 - 運動時の動き、AIで解析
東京農工大学の瀧山健准教授らが、人工知能（AI）を使って、運動時の体の動きを解析する技術を開発したことが紹介される。
日経産業新聞
自 2019年05月17日, 至 2019年05月17日 - 東京農工大、運動学習能力をタブレットで測定できるアプリ
日刊工業新聞
自 2016年06月30日, 至 2016年06月30日