Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive op...

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Autores principales:	Arne J Nagengast, Daniel A Braun, Daniel M Wolpert
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/c696cc47d2434dbaae178ca098298d21
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spelling	oai:doaj.org-article:c696cc47d2434dbaae178ca098298d212021-12-02T19:58:17ZRisk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.1553-734X1553-735810.1371/journal.pcbi.1000857https://doaj.org/article/c696cc47d2434dbaae178ca098298d212010-07-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20657657/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.Arne J NagengastDaniel A BraunDaniel M WolpertPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 6, Iss 7, p e1000857 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Arne J Nagengast Daniel A Braun Daniel M Wolpert Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
description	Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.
format	article
author	Arne J Nagengast Daniel A Braun Daniel M Wolpert
author_facet	Arne J Nagengast Daniel A Braun Daniel M Wolpert
author_sort	Arne J Nagengast
title	Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
title_short	Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
title_full	Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
title_fullStr	Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
title_full_unstemmed	Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
title_sort	risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/c696cc47d2434dbaae178ca098298d21
work_keys_str_mv	AT arnejnagengast risksensitiveoptimalfeedbackcontrolaccountsforsensorimotorbehaviorunderuncertainty AT danielabraun risksensitiveoptimalfeedbackcontrolaccountsforsensorimotorbehaviorunderuncertainty AT danielmwolpert risksensitiveoptimalfeedbackcontrolaccountsforsensorimotorbehaviorunderuncertainty
_version_	1718375802904510464

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

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