Humans Use Predictive Kinematic Models to Calibrate Visual Cues to Three-Dimensional Surface Slant
Identifieur interne : 001462 ( Pmc/Curation ); précédent : 001461; suivant : 001463Humans Use Predictive Kinematic Models to Calibrate Visual Cues to Three-Dimensional Surface Slant
Auteurs : Peter Scarfe ; Andrew GlennersterSource :
- The Journal of Neuroscience [ 0270-6474 ] ; 2014.
Abstract
When the sensory consequences of an action are systematically altered our brain can recalibrate the mappings between sensory cues and properties of our environment. This recalibration can be driven by both cue conflicts and altered sensory statistics, but neither mechanism offers a way for cues to be calibrated so they provide accurate information about the world, as sensory cues carry no information as to their own accuracy. Here, we explored whether sensory predictions based on internal physical models could be used to accurately calibrate visual cues to 3D surface slant. Human observers played a 3D kinematic game in which they adjusted the slant of a surface so that a moving ball would bounce off the surface and through a target hoop. In one group, the ball's bounce was manipulated so that the surface behaved as if it had a different slant to that signaled by visual cues. With experience of this altered bounce, observers recalibrated their perception of slant so that it was more consistent with the assumed laws of kinematics and physical behavior of the surface. In another group, making the ball spin in a way that could physically explain its altered bounce eliminated this pattern of recalibration. Importantly, both groups adjusted their behavior in the kinematic game in the same way, experienced the same set of slants, and were not presented with low-level cue conflicts that could drive the recalibration. We conclude that observers use predictive kinematic models to accurately calibrate visual cues to 3D properties of world.
Url:
DOI: 10.1523/JNEUROSCI.1000-14.2014
PubMed: 25080598
PubMed Central: 4115143
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Peter Scarfe<affiliation><nlm:aff id="aff1">School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, United Kingdom RG6 6AL</nlm:aff>
<wicri:noCountry code="subfield">United Kingdom RG6 6AL</wicri:noCountry>
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<affiliation><nlm:aff id="aff1">School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, United Kingdom RG6 6AL</nlm:aff>
<wicri:noCountry code="subfield">United Kingdom RG6 6AL</wicri:noCountry>
</affiliation>
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<front><div type="abstract" xml:lang="en"><p>When the sensory consequences of an action are systematically altered our brain can recalibrate the mappings between sensory cues and properties of our environment. This recalibration can be driven by both cue conflicts and altered sensory statistics, but neither mechanism offers a way for cues to be calibrated so they provide accurate information about the world, as sensory cues carry no information as to their own accuracy. Here, we explored whether sensory predictions based on internal physical models could be used to accurately calibrate visual cues to 3D surface slant. Human observers played a 3D kinematic game in which they adjusted the slant of a surface so that a moving ball would bounce off the surface and through a target hoop. In one group, the ball's bounce was manipulated so that the surface behaved as if it had a different slant to that signaled by visual cues. With experience of this altered bounce, observers recalibrated their perception of slant so that it was more consistent with the assumed laws of kinematics and physical behavior of the surface. In another group, making the ball spin in a way that could physically explain its altered bounce eliminated this pattern of recalibration. Importantly, both groups adjusted their behavior in the kinematic game in the same way, experienced the same set of slants, and were not presented with low-level cue conflicts that could drive the recalibration. We conclude that observers use predictive kinematic models to accurately calibrate visual cues to 3D properties of world.</p>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Neurosci</journal-id>
<journal-id journal-id-type="iso-abbrev">J. Neurosci</journal-id>
<journal-id journal-id-type="hwp">jneuro</journal-id>
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<article-categories><subj-group subj-group-type="heading"><subject>Articles</subject>
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<title-group><article-title>Humans Use Predictive Kinematic Models to Calibrate Visual Cues to Three-Dimensional Surface Slant</article-title>
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<contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Scarfe</surname>
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<author-notes><corresp>Correspondence should be addressed to Dr. Peter Scarfe,
<addr-line>School of Psychology and Clinical Language Sciences, University of Reading, Early Gate, Whiteknights Road, Reading, Berkshire, UK RG6 6AL.</addr-line>
<email>p.scarfe@reading.ac.uk</email>
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<fn fn-type="con"><p>Author contributions: P.S. and A.G. designed research; P.S. performed research; P.S. analyzed data; P.S. and A.G. wrote the paper.</p>
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<pub-date pub-type="ppub"><day>30</day>
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<year>2014</year>
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<volume>34</volume>
<issue>31</issue>
<fpage>10394</fpage>
<lpage>10401</lpage>
<history><date date-type="received"><day>11</day>
<month>3</month>
<year>2014</year>
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<date date-type="rev-recd"><day>17</day>
<month>6</month>
<year>2014</year>
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<date date-type="accepted"><day>23</day>
<month>6</month>
<year>2014</year>
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<permissions><copyright-statement>Copyright © 2014 Scarfe and Glennerster</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access"><license-p>This article is freely available online through the <ext-link ext-link-type="uri" xlink:href="http://www.jneurosci.org/cgi/content/full/34/31/10394"><italic>J Neurosci</italic>
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<self-uri xlink:title="pdf" xlink:type="simple" xlink:href="zns03114010394.pdf"></self-uri>
<abstract><p>When the sensory consequences of an action are systematically altered our brain can recalibrate the mappings between sensory cues and properties of our environment. This recalibration can be driven by both cue conflicts and altered sensory statistics, but neither mechanism offers a way for cues to be calibrated so they provide accurate information about the world, as sensory cues carry no information as to their own accuracy. Here, we explored whether sensory predictions based on internal physical models could be used to accurately calibrate visual cues to 3D surface slant. Human observers played a 3D kinematic game in which they adjusted the slant of a surface so that a moving ball would bounce off the surface and through a target hoop. In one group, the ball's bounce was manipulated so that the surface behaved as if it had a different slant to that signaled by visual cues. With experience of this altered bounce, observers recalibrated their perception of slant so that it was more consistent with the assumed laws of kinematics and physical behavior of the surface. In another group, making the ball spin in a way that could physically explain its altered bounce eliminated this pattern of recalibration. Importantly, both groups adjusted their behavior in the kinematic game in the same way, experienced the same set of slants, and were not presented with low-level cue conflicts that could drive the recalibration. We conclude that observers use predictive kinematic models to accurately calibrate visual cues to 3D properties of world.</p>
</abstract>
<kwd-group><kwd>3D slant</kwd>
<kwd>calibration</kwd>
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