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A data-driven approach to decompose motion data into task-relevant and task-irrelevant components in categorical outcome
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 sp...
Autores principales: | Furuki, Daisuke, Takiyama, Ken |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7015904/ https://www.ncbi.nlm.nih.gov/pubmed/32051444 http://dx.doi.org/10.1038/s41598-020-59257-z |
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