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dc.contributor.authorJia, Xiaoxuan
dc.contributor.authorHong, Ha
dc.contributor.authorDiCarlo, James J
dc.date.accessioned2021-11-22T19:39:30Z
dc.date.available2021-11-22T19:39:30Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/138201
dc.description.abstract<jats:p>Temporal continuity of object identity is a feature of natural visual input and is potentially exploited – in an unsupervised manner – by the ventral visual stream to build the neural representation in inferior temporal (IT) cortex. Here, we investigated whether plasticity of individual IT neurons underlies human core object recognition behavioral changes induced with unsupervised visual experience. We built a single-neuron plasticity model combined with a previously established IT population-to-recognition-behavior-linking model to predict human learning effects. We found that our model, after constrained by neurophysiological data, largely predicted the mean direction, magnitude, and time course of human performance changes. We also found a previously unreported dependency of the observed human performance change on the initial task difficulty. This result adds support to the hypothesis that tolerant core object recognition in human and non-human primates is instructed – at least in part – by naturally occurring unsupervised temporal contiguity experience.</jats:p>en_US
dc.language.isoen
dc.publishereLife Sciences Publications, Ltden_US
dc.relation.isversionof10.7554/ELIFE.60830en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceeLifeen_US
dc.titleUnsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortexen_US
dc.typeArticleen_US
dc.identifier.citationJia, Xiaoxuan, Hong, Ha and DiCarlo, James J. 2021. "Unsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortex." eLife, 10.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences
dc.contributor.departmentMcGovern Institute for Brain Research at MIT
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technology
dc.contributor.departmentCenter for Brains, Minds, and Machines
dc.relation.journaleLifeen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-11-22T19:37:03Z
dspace.orderedauthorsJia, X; Hong, H; DiCarlo, JJen_US
dspace.date.submission2021-11-22T19:37:04Z
mit.journal.volume10en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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