about
Robotic neurorehabilitation: a computational motor learning perspectiveReview of control strategies for robotic movement training after neurologic injuryNeuromechanical principles underlying movement modularity and their implications for rehabilitationRethinking motor learning and savings in adaptation paradigms: model-free memory for successful actions combines with internal models.Augmented dynamics and motor exploration as training for stroke.Persistence of motor memories reflects statistics of the learning event.Optimal Schedules in Multitask Motor Learning.Not all choices are created equal: Task-relevant choices enhance motor learning compared to task-irrelevant choices.On the Role of Error in Motor Learning.A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition.
P2860
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P2860
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
2008年论文
@zh
2008年论文
@zh-cn
name
Active learning: learning a motor skill without a coach
@en
type
label
Active learning: learning a motor skill without a coach
@en
prefLabel
Active learning: learning a motor skill without a coach
@en
P2860
P356
P1476
Active learning: learning a motor skill without a coach
@en
P2093
Reza Shadmehr
Vincent S Huang
P2860
P304
P356
10.1152/JN.01095.2007
P407
P577
2008-05-28T00:00:00Z