Information Services banner Edinburgh Research Archive The University of Edinburgh crest

Edinburgh Research Archive >
Informatics, School of >
Informatics Publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1842/3657

This item has been viewed 32 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Unifying the Sensory and Motor Components of Sensorimotor Adaptation-Spotlight.pdf37.97 kBAdobe PDFView/Open
Unifying the Sensory and Motor Components of Sensorimotor Adaptation-Poster.pdf430.01 kBAdobe PDFView/Open
Unifying the Sensory and Motor Components of Sensorimotor Adaptation.pdf376.78 kBAdobe PDFView/Open
Title: Unifying the Sensory and Motor Components of Sensorimotor Adaptation
Authors: Haith, Adrian
Jackson, Carl
Miall, Chris
Vijayakumar, Sethu
Issue Date: 2008
Journal Title: Proc. Advances in Neural Information Processing Systems (NIPS '08)
Abstract: Adaptation of visually guided reaching movements in novel visuomotor environments (e.g. wearing prism goggles) comprises not only motor adaptation but also substantial sensory adaptation, corresponding to shifts in the perceived spatial location of visual and proprioceptive cues. Previous computational models of the sensory component of visuomotor adaptation have assumed that it is driven purely by the discrepancy introduced between visual and proprioceptive estimates of hand position and is independent of any motor component of adaptation. We instead propose a unified model in which sensory and motor adaptation are jointly driven by optimal Bayesian estimation of the sensory and motor contributions to perceived errors. Our model is able to account for patterns of performance errors during visuomotor adaptation as well as the subsequent perceptual aftereffects. This unified model also makes the surprising prediction that force field adaptation will elicit similar perceptual shifts, even though there is never any discrepancy between visual and proprioceptive observations. We confirm this prediction with an experiment.
URI: http://books.nips.cc/nips21.html
http://hdl.handle.net/1842/3657
Appears in Collections:Informatics Publications

Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2013, and/or the original authors. Privacy and Cookies Policy