How haptic size sensations improve distance perception.
Identifieur interne : 000D37 ( PubMed/Checkpoint ); précédent : 000D36; suivant : 000D38How haptic size sensations improve distance perception.
Auteurs : Peter W. Battaglia [États-Unis] ; Daniel Kersten ; Paul R. SchraterSource :
- PLoS computational biology [ 1553-7358 ] ; 2011.
English descriptors
- KwdEn :
- MESH :
- methods : Computational Biology.
- physiology : Distance Perception, Touch Perception.
- Adult, Bayes Theorem, Cognition, Decision Making, Humans.
Abstract
Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual "posterior sampling". In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information.
DOI: 10.1371/journal.pcbi.1002080
PubMed: 21738457
Affiliations:
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pubmed:21738457Le document en format XML
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<front><div type="abstract" xml:lang="en">Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual "posterior sampling". In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information.</div>
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<CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Nature. 2002 Jan 24;415(6870):429-33</RefSource>
<PMID Version="1">11807554</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Cogn Sci. 2014 May-Jun;38(4):599-637</RefSource>
<PMID Version="1">24467492</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Annu Rev Psychol. 2004;55:271-304</RefSource>
<PMID Version="1">14744217</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Neurophysiol. 2004 Feb;91(2):1050-63</RefSource>
<PMID Version="1">14561687</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Am J Psychol. 1966 Jun;79(2):234-41</RefSource>
<PMID Version="1">5915906</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Am J Psychol. 1970 Mar;83(1):40-54</RefSource>
<PMID Version="1">5449391</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Exp Brain Res. 1970 Nov 26;11(4):411-30</RefSource>
<PMID Version="1">5496938</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Perception. 1973;2(3):267-85</RefSource>
<PMID Version="1">4794124</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Child Dev. 1982 Oct;53(5):1285-90</RefSource>
<PMID Version="1">7140431</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Vision Res. 1992 Aug;32(8):1447-60</RefSource>
<PMID Version="1">1455718</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Vision Res. 1999 Mar;39(5):975-86</RefSource>
<PMID Version="1">10341949</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Am J Psychol. 1951 Jan;64(1):54-67</RefSource>
<PMID Version="1">14819380</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Psychol Rev. 1953 Jul;60(4):223-31</RefSource>
<PMID Version="1">13089000</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Psychol Bull. 1961 Nov;58:491-514</RefSource>
<PMID Version="1">13890453</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Am J Psychol. 1963 Dec;76:537-53</RefSource>
<PMID Version="1">14082652</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Trends Neurosci. 2004 Dec;27(12):712-9</RefSource>
<PMID Version="1">15541511</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Trends Cogn Sci. 2006 Jul;10(7):319-26</RefSource>
<PMID Version="1">16807063</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Proc Biol Sci. 2006 Sep 7;273(1598):2159-68</RefSource>
<PMID Version="1">16901835</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2007;2(9):e943</RefSource>
<PMID Version="1">17895984</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neural Comput. 2007 Dec;19(12):3335-55</RefSource>
<PMID Version="1">17970656</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Vis. 2007;7(5):7.1-14</RefSource>
<PMID Version="1">18217847</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Vis. 2008;8(5):12.1-19</RefSource>
<PMID Version="1">18842083</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Trends Cogn Sci. 2010 Mar;14(3):119-30</RefSource>
<PMID Version="1">20153683</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2010 Mar;6(3):e1000697</RefSource>
<PMID Version="1">20221263</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2010;6(8). pii: e1000871. doi: 10.1371/journal.pcbi.1000871</RefSource>
<PMID Version="1">20700493</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Opt Soc Am A Opt Image Sci Vis. 2003 Jul;20(7):1391-7</RefSource>
<PMID Version="1">12868643</PMID>
</CommentsCorrections>
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