Dissociable effects of the implicit and explicit memory systems on learning control of reaching
Identifieur interne : 000891 ( Ncbi/Merge ); précédent : 000890; suivant : 000892Dissociable effects of the implicit and explicit memory systems on learning control of reaching
Auteurs : Eun Jung Hwang ; Maurice A. Smith ; Reza ShadmehrSource :
- Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale [ 0014-4819 ] ; 2006.
Abstract
Adaptive control of reaching depends on internal models that associate states in which the limb experienced a force perturbation with motor commands that can compensate for it. Limb state can be sensed via both vision and proprioception. However, adaptation of reaching in novel dynamics results in generalization in the intrinsic coordinates of the limb, suggesting that the proprioceptive states in which the limb was perturbed dominate representation of limb state. To test this hypothesis, we considered a task where position of the hand during a reach was correlated with patterns of force perturbation. This correlation could be sensed via vision, proprioception, or both. As predicted, when the correlations could be sensed only via proprioception, learning was significantly better as compared to when the correlations could only be sensed through vision. We found that learning with visual correlations resulted in subjects who could verbally describe the patterns of perturbations but this awareness was never observed in subjects who learned the task with only proprioceptive correlations. We manipulated the relative values of the visual and proprioceptive parameters and found that the probability of becoming aware strongly depended on the correlations that subjects could visually observe. In all conditions, aware subjects demonstrated a small but significant advantage in their ability to adapt their motor commands. Proprioceptive correlations produced an internal model that strongly influenced reaching performance yet did not lead to awareness. Visual correlations strongly increased the probability of becoming aware, yet had a much smaller but still significant effect on reaching performance. Therefore, practice resulted in acquisition of both implicit and explicit internal models.
Url:
DOI: 10.1007/s00221-006-0391-0
PubMed: 16506003
PubMed Central: 1628349
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PMC:1628349Le document en format XML
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<author><name sortKey="Hwang, Eun Jung" sort="Hwang, Eun Jung" uniqKey="Hwang E" first="Eun Jung" last="Hwang">Eun Jung Hwang</name>
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<author><name sortKey="Smith, Maurice A" sort="Smith, Maurice A" uniqKey="Smith M" first="Maurice A." last="Smith">Maurice A. Smith</name>
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<author><name sortKey="Shadmehr, Reza" sort="Shadmehr, Reza" uniqKey="Shadmehr R" first="Reza" last="Shadmehr">Reza Shadmehr</name>
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<front><div type="abstract" xml:lang="en"><p id="P1">Adaptive control of reaching depends on internal models that associate states in which the limb experienced a force perturbation with motor commands that can compensate for it. Limb state can be sensed via both vision and proprioception. However, adaptation of reaching in novel dynamics results in generalization in the intrinsic coordinates of the limb, suggesting that the proprioceptive states in which the limb was perturbed dominate representation of limb state. To test this hypothesis, we considered a task where position of the hand during a reach was correlated with patterns of force perturbation. This correlation could be sensed via vision, proprioception, or both. As predicted, when the correlations could be sensed only via proprioception, learning was significantly better as compared to when the correlations could only be sensed through vision. We found that learning with visual correlations resulted in subjects who could verbally describe the patterns of perturbations but this awareness was never observed in subjects who learned the task with only proprioceptive correlations. We manipulated the relative values of the visual and proprioceptive parameters and found that the probability of becoming aware strongly depended on the correlations that subjects could visually observe. In all conditions, aware subjects demonstrated a small but significant advantage in their ability to adapt their motor commands. Proprioceptive correlations produced an internal model that strongly influenced reaching performance yet did not lead to awareness. Visual correlations strongly increased the probability of becoming aware, yet had a much smaller but still significant effect on reaching performance. Therefore, practice resulted in acquisition of both implicit and explicit internal models.</p>
</div>
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<front><journal-meta><journal-id journal-id-type="nlm-journal-id">0043312</journal-id>
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<journal-id journal-id-type="nlm-ta">Exp Brain Res</journal-id>
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<title-group><article-title>Dissociable effects of the implicit and explicit memory systems on learning control of reaching</article-title>
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<contrib-group><contrib contrib-type="author"><name><surname>Hwang</surname>
<given-names>Eun Jung</given-names>
</name>
<xref rid="FN2" ref-type="author-notes">*</xref>
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<contrib contrib-type="author"><name><surname>Smith</surname>
<given-names>Maurice A.</given-names>
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<contrib contrib-type="author"><name><surname>Shadmehr</surname>
<given-names>Reza</given-names>
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<xref rid="FN1" ref-type="author-notes"></xref>
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<aff id="A1">Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205</aff>
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<author-notes><corresp id="FN1"><bold>Send correspondence to:</bold>
Reza Shadmehr, Johns Hopkins School of Medicine, 419 Traylor Building, 720 Rutland Ave, Baltimore MD 21205. Phone: 410-614-3424, Fax: 410-614-9890, email: <email>reza@bme.jhu.edu</email>
.</corresp>
<fn id="FN2" fn-type="present-address"><label>*</label>
<p>Eun Jung Hwang’s current address: Division of Biology 216-76, California Institute of Technology, Pasadena, CA 91125.</p>
</fn>
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<pub-date pub-type="nihms-submitted"><day>3</day>
<month>4</month>
<year>2006</year>
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<pub-date pub-type="epub"><day>28</day>
<month>2</month>
<year>2006</year>
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<pub-date pub-type="ppub"><month>8</month>
<year>2006</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>30</day>
<month>10</month>
<year>2006</year>
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<volume>173</volume>
<issue>3</issue>
<fpage>425</fpage>
<lpage>437</lpage>
<abstract><p id="P1">Adaptive control of reaching depends on internal models that associate states in which the limb experienced a force perturbation with motor commands that can compensate for it. Limb state can be sensed via both vision and proprioception. However, adaptation of reaching in novel dynamics results in generalization in the intrinsic coordinates of the limb, suggesting that the proprioceptive states in which the limb was perturbed dominate representation of limb state. To test this hypothesis, we considered a task where position of the hand during a reach was correlated with patterns of force perturbation. This correlation could be sensed via vision, proprioception, or both. As predicted, when the correlations could be sensed only via proprioception, learning was significantly better as compared to when the correlations could only be sensed through vision. We found that learning with visual correlations resulted in subjects who could verbally describe the patterns of perturbations but this awareness was never observed in subjects who learned the task with only proprioceptive correlations. We manipulated the relative values of the visual and proprioceptive parameters and found that the probability of becoming aware strongly depended on the correlations that subjects could visually observe. In all conditions, aware subjects demonstrated a small but significant advantage in their ability to adapt their motor commands. Proprioceptive correlations produced an internal model that strongly influenced reaching performance yet did not lead to awareness. Visual correlations strongly increased the probability of becoming aware, yet had a much smaller but still significant effect on reaching performance. Therefore, practice resulted in acquisition of both implicit and explicit internal models.</p>
</abstract>
<kwd-group><kwd>reaching</kwd>
<kwd>arm movements</kwd>
<kwd>awareness</kwd>
<kwd>adaptation</kwd>
<kwd>force fields</kwd>
<kwd>vision</kwd>
<kwd>proprioception</kwd>
<kwd>computational models</kwd>
<kwd>motor control</kwd>
<kwd>motor learning</kwd>
</kwd-group>
<contract-num rid="NS1">R01 NS037422-07</contract-num>
<contract-sponsor id="NS1">National Institute of Neurological Disorders and Stroke : NINDS</contract-sponsor>
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