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dc.contributor.authorBarbu, Andrei
dc.contributor.authorNarayanaswamy, Siddharth
dc.contributor.authorXiong, Caiming
dc.contributor.authorCorso, Jason J.
dc.contributor.authorFellbaum, Christiane D.
dc.contributor.authorHanson, Catherine
dc.contributor.authorHanson, Stephen Jose
dc.contributor.authorHelie, Sebastien
dc.contributor.authorMalaia, Evguenia
dc.contributor.authorPearlmutter, Barak A.
dc.contributor.authorSiskind, Jeffrey Mark
dc.contributor.authorTalavage, Thomas Michael
dc.contributor.authorWilbur, Ronnie B.
dc.date.accessioned2015-12-10T18:58:04Z
dc.date.available2015-12-10T18:58:04Z
dc.date.issued2014-07-14
dc.identifier.urihttp://hdl.handle.net/1721.1/100175
dc.description.abstractHow does the human brain represent simple compositions of constituents: actors, verbs, objects, directions, and locations? Subjects viewed videos during neuroimaging (fMRI) sessions from which sentential descriptions of those videos were identified by decoding the brain representations based only on their fMRI activation patterns. Constituents (e.g., fold and shirt) were independently decoded from a single presentation. Independent constituent classification was then compared to joint classification of aggregate concepts (e.g., fold -shirt); results were similar as measured by accuracy and correlation. The brain regions used for independent constituent classification are largely disjoint and largely cover those used for joint classification. This allows recovery of sentential descriptions of stimulus videos by composing the results of the independent constituent classifiers. Furthermore, classifiers trained on the words one set of subjects think of when watching a video can recognize sentences a different subject thinks of when watching a different video.en_US
dc.description.sponsorshipThis work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.en_US
dc.language.isoen_USen_US
dc.publisherCenter for Brains, Minds and Machines (CBMM), arXiven_US
dc.relation.ispartofseriesCBMM Memo Series;011
dc.rightsAttribution-NonCommercial 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/us/*
dc.subjectComputer Languageen_US
dc.subjectLinguisticsen_US
dc.subjectLanguageen_US
dc.subjectNeuroscienceen_US
dc.subjectVision and Languageen_US
dc.titleThe Compositional Nature of Event Representations in the Human Brainen_US
dc.typeTechnical Reporten_US
dc.typeWorking Paperen_US
dc.typeOtheren_US
dc.identifier.citationarXiv:1505.06670v1en_US


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