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dc.contributor.authorLipkin, Benjamin
dc.contributor.authorTuckute, Greta
dc.contributor.authorAffourtit, Josef
dc.contributor.authorSmall, Hannah
dc.contributor.authorMineroff, Zachary
dc.contributor.authorKean, Hope
dc.contributor.authorJouravlev, Olessia
dc.contributor.authorRakocevic, Lara
dc.contributor.authorPritchett, Brianna
dc.contributor.authorSiegelman, Matthew
dc.contributor.authorHoeflin, Caitlyn
dc.contributor.authorPongos, Alvincé
dc.contributor.authorBlank, Idan A
dc.contributor.authorStruhl, Melissa Kline
dc.contributor.authorIvanova, Anna
dc.contributor.authorShannon, Steven
dc.contributor.authorSathe, Aalok
dc.contributor.authorHoffmann, Malte
dc.contributor.authorNieto-Castañón, Alfonso
dc.contributor.authorFedorenko, Evelina
dc.date.accessioned2023-03-27T12:53:04Z
dc.date.available2023-03-27T12:53:04Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/1721.1/148763
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>Two analytic traditions characterize fMRI language research. One relies on averaging activations across individuals. This approach has limitations: because of inter-individual variability in the locations of language areas, any given voxel/vertex in a common brain space is part of the language network in some individuals but in others, may belong to a distinct network. An alternative approach relies on identifying language areas in each individual using a functional ‘localizer’. Because of its greater sensitivity, functional resolution, and interpretability, functional localization is gaining popularity, but it is not always feasible, and cannot be applied retroactively to past studies. To bridge these disjoint approaches, we created a <jats:italic>probabilistic functional atlas</jats:italic> using fMRI data for an extensively validated language localizer in 806 individuals. This atlas enables estimating the probability that any given location in a common space belongs to the language network, and thus can help interpret group-level activation peaks and lesion locations, or select voxels/electrodes for analysis. More meaningful comparisons of findings across studies should increase robustness and replicability in language research.</jats:p>en_US
dc.language.isoen
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionof10.1038/S41597-022-01645-3en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceScientific Reportsen_US
dc.titleProbabilistic atlas for the language network based on precision fMRI data from >800 individualsen_US
dc.typeArticleen_US
dc.identifier.citationLipkin, Benjamin, Tuckute, Greta, Affourtit, Josef, Small, Hannah, Mineroff, Zachary et al. 2022. "Probabilistic atlas for the language network based on precision fMRI data from >800 individuals." Scientific Data, 9 (1).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.relation.journalScientific Dataen_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.updated2023-03-27T12:46:43Z
dspace.orderedauthorsLipkin, B; Tuckute, G; Affourtit, J; Small, H; Mineroff, Z; Kean, H; Jouravlev, O; Rakocevic, L; Pritchett, B; Siegelman, M; Hoeflin, C; Pongos, A; Blank, IA; Struhl, MK; Ivanova, A; Shannon, S; Sathe, A; Hoffmann, M; Nieto-Castañón, A; Fedorenko, Een_US
dspace.date.submission2023-03-27T12:46:47Z
mit.journal.volume9en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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