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dc.contributor.authorDobs, Katharina B
dc.contributor.authorIsik, Leyla
dc.contributor.authorPantazis, Dimitrios
dc.contributor.authorKanwisher, Nancy
dc.date.accessioned2020-08-31T21:02:04Z
dc.date.available2020-08-31T21:02:04Z
dc.date.issued2019-03
dc.date.submitted2018-10
dc.identifier.issn2041-1723
dc.identifier.urihttps://hdl.handle.net/1721.1/126848
dc.description.abstractWithin a fraction of a second of viewing a face, we have already determined its gender, age and identity. A full understanding of this remarkable feat will require a characterization of the computational steps it entails, along with the representations extracted at each. Here, we used magnetoencephalography (MEG) to measure the time course of neural responses to faces, thereby addressing two fundamental questions about how face processing unfolds over time. First, using representational similarity analysis, we found that facial gender and age information emerged before identity information, suggesting a coarse-to-fine processing of face dimensions. Second, identity and gender representations of familiar faces were enhanced very early on, suggesting that the behavioral benefit for familiar faces results from tuning of early feed-forward processing mechanisms. These findings start to reveal the time course of face processing in humans, and provide powerful new constraints on computational theories of face perception. ©2019, The Author(s).en_US
dc.description.sponsorshipFeodor-Lynen postdoctoral fellowship of the Humboldt Foundationen_US
dc.description.sponsorshipNIH grant (DP1HD091947)en_US
dc.language.isoen
dc.publisherSpringer Natureen_US
dc.relation.isversionofhttps://dx.doi.org/10.1038/s41467-019-09239-1en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleHow face perception unfolds over timeen_US
dc.typeArticleen_US
dc.identifier.citationDobs, Katharina et al., "How face perception unfolds over time." Nature Communications 10, 1 (March 2019): no. 1258 doi. 10.1038/s41467-019-09239-1 ©2019 Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMcGovern Institute for Brain Research at MITen_US
dc.contributor.departmentCenter for Brains, Minds, and Machinesen_US
dc.relation.journalNature Communicationsen_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.updated2019-07-18T14:20:11Z
dspace.date.submission2019-07-18T14:20:12Z
mit.journal.volume10en_US
mit.journal.issue1en_US
mit.metadata.statusComplete


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