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.

Bibliographic Details
Main Authors: Aaron L. Wong, Adrian M. Haith
Format: Article
Language:English
Published: Nature Publishing Group 2017-03-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/ncomms14624