Uncertainty of Feedback and State Estimation Determines the Speed of Motor Adaptation
Identifieur interne : 003529 ( Main/Merge ); précédent : 003528; suivant : 003530Uncertainty of Feedback and State Estimation Determines the Speed of Motor Adaptation
Auteurs : Kunlin Wei [République populaire de Chine, États-Unis] ; Konrad Körding [États-Unis]Source :
- Frontiers in Computational Neuroscience [ 1662-5188 ] ; 2010.
Abstract
Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation.
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DOI: 10.3389/fncom.2010.00011
PubMed: 20485466
PubMed Central: 2871692
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type="wicri:Area/Main/Merge">003529</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Uncertainty of Feedback and State Estimation Determines the Speed of Motor Adaptation</title><author><name sortKey="Wei, Kunlin" sort="Wei, Kunlin" uniqKey="Wei K" first="Kunlin" last="Wei">Kunlin Wei</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Department of Psychology, Peking University</institution><country>Beijing, China</country></nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Departments of Physiology, Physical Medicine and Rehabilitation, and Applied Mathematics, Northwestern University</institution><country>Chicago, IL, USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Bayesian Behavior Lab, Sensory Motor Performance Program, Rehabilitation Institute of Chicago</institution><country>IL, USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="Kording, Konrad" sort="Kording, Konrad" uniqKey="Kording K" first="Konrad" last="Körding">Konrad Körding</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Departments of Physiology, Physical Medicine and Rehabilitation, and Applied Mathematics, Northwestern University</institution><country>Chicago, IL, USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Bayesian Behavior Lab, Sensory Motor Performance Program, Rehabilitation Institute of Chicago</institution><country>IL, USA</country></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author></analytic><series><title level="j">Frontiers in Computational Neuroscience</title><idno type="eISSN">1662-5188</idno><imprint><date when="2010">2010</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Alais, D" uniqKey="Alais D">D. Alais</name></author><author><name sortKey="Burr, D" uniqKey="Burr D">D. Burr</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Baddeley, R J" uniqKey="Baddeley R">R. J. Baddeley</name></author><author><name sortKey="Ingram, H A" uniqKey="Ingram H">H. A. Ingram</name></author><author><name sortKey="Miall, R C" uniqKey="Miall R">R. C. Miall</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Behrens, T" uniqKey="Behrens T">T. Behrens</name></author><author><name sortKey="Woolrich, M" uniqKey="Woolrich M">M. Woolrich</name></author><author><name sortKey="Walton, M" uniqKey="Walton M">M. 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Sittig</name></author><author><name sortKey="Gon, J J" uniqKey="Gon J">J. J. Gon</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Von Helmholtz, H F" uniqKey="Von Helmholtz H">H. F. von Helmholtz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wei, K" uniqKey="Wei K">K. Wei</name></author><author><name sortKey="Kording, K" uniqKey="Kording K">K. Kording</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wolpert, D M" uniqKey="Wolpert D">D. M. Wolpert</name></author><author><name sortKey="Ghahramani, Z" uniqKey="Ghahramani Z">Z. Ghahramani</name></author><author><name sortKey="Jordan, M I" uniqKey="Jordan M">M. I. Jordan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zemel, R S" uniqKey="Zemel R">R. S. Zemel</name></author><author><name sortKey="Dayan, P" uniqKey="Dayan P">P. 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