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Advances in Neural Information Processing Systems 21

dc.contributor.authorNatarajan, Rama
dc.contributor.authorMurray, Iain
dc.contributor.authorShams, Ladan
dc.contributor.authorZemel, Richard
dc.date.accessioned2011-01-13T17:40:25Z
dc.date.available2011-01-13T17:40:25Z
dc.date.issued2009en
dc.identifier.urihttp://books.nips.cc/papers/files/nips21/NIPS2008_0865.pdfen
dc.identifier.urihttp://hdl.handle.net/1842/4589
dc.description.abstractWe explore a recently proposed mixture model approach to understanding interactions between conflicting sensory cues. Alternative model formulations, differing in their sensory noise models and inference methods, are compared based on their fit to experimental data. Heavy-tailed sensory likelihoods yield a better description of the subjects' response behavior than standard Gaussian noise models. We study the underlying cause for this result, and then present several testable predictions of these models.en
dc.language.isoenen
dc.titleCharacterizing response behavior in multisensory perception with conflicting cuesen
dc.typeConference Paperen
rps.titleAdvances in Neural Information Processing Systems 21en
dc.extent.noOfPages1153-1160en
dc.date.updated2011-01-13T17:40:26Z
dc.date.openingDate2008-12-08
dc.date.closingDate2008-12-11


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