Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368950
Title: Context estimation in sensorimotor control
Author: Vetter, Philipp
ISNI:       0000 0001 3546 7987
Awarding Body: University of London
Current Institution: University College London (University of London)
Date of Award: 2001
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Abstract:
Human motor behaviour is remarkably accurate and appropriate even though the properties of our own bodies as well as the objects we interact with vary over time. To adjust appropriately, the motor system has to estimate the context, that is the properties of objects in the world and the prevailing environmental conditions. This thesis examines how we estimate the context given that the context is nonstationary, it can change both deterministically and stochastically over time, and that information about the context, such as prior information and sensory feedback, may be incomplete or noisy. Psychophysical and brain imaging studies are described, showing that to determine the current context the central nervous system uses information from both prior knowledge of how the context might evolve over time and from the comparison of predicted and actual sensory feedback. A computational model is presented of how these two sources of information are modelled and combined within the central nervous system to derive an accurate estimate of the context that is then used to appropriately adjust the motor command selection. A modelling study explores how context estimation may be used to learn and select appropriate controllers within a modular architecture. The model suggests that prediction should precede control during motor learning and this is confirmed psychophysically. The experimental findings are discussed with regard to their computational significance and their possible neural representation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.368950  DOI: Not available
Keywords: Physiology
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