Motor planning flexibly optimizes performance under uncertainty about task goals
It is thought that, when goals are uncertain, actions are generated by averaging multiple possible movement plans. Here the authors show that movement planning under uncertainty instead varies flexibly depending on the speed of the movement in order to maximize success.
Guardado en:
Autores principales: | Aaron L. Wong, Adrian M. Haith |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2017
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Materias: | |
Acceso en línea: | https://doaj.org/article/44411f17e2a5436c9470430db37f85a7 |
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