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Probabilistic models of sensorimotor control and decision making| old_uid | 13790 |
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| title | Probabilistic models of sensorimotor control and decision making |
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| start_date | 2014/04/07 |
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| schedule | 11h-12h30 |
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| online | no |
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| summary | The effortless ease with which humans move our arms, our eyes, even our lips when we speak masks the true complexity of the control processes involved. This is evident when we try to build machines to perform human control tasks. While computers can now beat grandmasters at chess, no computer can yet control a robot to manipulate a chess piece with the dexterity of a six-year-old child. I will review our work on how the humans learn to make skilled movements covering probabilistic models of learning, including Bayesian and structural learning. I will also review our recent work showing the intimate interactions between decision making and sensorimotor control processes. This includes the relation between vacillation and changes of mind in decision making and the bidirectional flow of information between elements of decision formations such as accumulated evidence and motor processes such as reflex gains. Taken together these studies show that probabilistic models play a fundamental role in human sensorimotor control. |
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| responsibles | Rämä, Izard |
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