Author

Yasuharu Koike

Tokyo Institute of TechnologyORCID 0000-0002-8169-0044Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:cell type annotation· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Organism:human· 1

Frequent Co-Authors

Nicolas SchweighoferiD· 2 shared Victor R. BarradasiD· 2 shared Atsushi TakagiiD· 1 shared Etienne BurdetiD· 1 shared Hiroaki GomiiD· 1 shared Jason J. KutchiD· 1 shared Toshihiro KawaseiD· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 9 mutual co-author links

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2 shared papersNeuroscience

Nicolas SchweighoferORCID

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3 papers

Recent·Most cited

Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks

Victor R. Barradas, Yasuharu Koike, Nicolas Schweighofer

The paper analyzes the speed of learning inverse models in motor tasks using theoretical and experimental approaches, finding that task geometry and target distribution influence learning speed.

Neural Networks · Oct 31, 2023Peer-reviewedNeuroscience

A model predictive control strategy to regulate movements and interactions

Atsushi Takagi, Hiroaki Gomi, Etienne Burdet, Yasuharu Koike

This paper introduces a Model Predictive Control strategy that regulates both movement and interaction control, demonstrating its ability to produce human-like movements and handle nonlinear dynamics.

bioRxiv · Aug 24, 2022 · PreprintNeuroscience

When 90% of the variance is not enough: residual EMG from muscle synergy extraction influences task performance

Victor R. Barradas, Jason J. Kutch, Toshihiro Kawase, Yasuharu Koike, Nicolas Schweighofer

This study shows that residual muscle activity not explained by synergy extraction significantly affects motor task performance, challenging the assumption that it is noise.

Journal of Neurophysiology · Apr 8, 2020Peer-reviewedNeuroscience