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- W2124041771 abstract "When one moves one’s hand from one point to another, the brain guides the arm by relying on neural structures that estimate the physical dynamics of the task. For example, if one is about to lift a bottle of milk that appears full rather than empty, the brain takes into account the subtle changes in the dynamics of the task and this is reflected in the altered motor commands. The neural structures that compute the task’s dynamics are “internal models” that transform the desired motion into motor commands. Internal models are learned with practice and are a fundamental part of voluntary motor control. What do internal models compute, and which neural structures perform that computation? We approach these problems by considering a task where physical dynamics of reaching movements are altered by force fields that act on the hand. Experiments by a number of laboratories on this paradigm suggest that internal models are sensorimotor transformations that map a desired sensory state" @default.
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- W2124041771 date "2004-12-28" @default.
- W2124041771 modified "2023-09-27" @default.
- W2124041771 title "Learning Dynamics of Reaching" @default.
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- W2124041771 doi "https://doi.org/10.1201/9780203503584.ch11" @default.
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