Show simple item record

dc.contributor.authorNorman-Haignere, Samuel Victor
dc.contributor.authorMcDermott, Joshua H.
dc.date.accessioned2019-02-21T21:19:17Z
dc.date.available2019-02-21T21:19:17Z
dc.date.issued2018-12
dc.date.submitted2017-12
dc.identifier.issn1545-7885
dc.identifier.urihttp://hdl.handle.net/1721.1/120532
dc.description.abstractA central goal of sensory neuroscience is to construct models that can explain neural responses to natural stimuli. As a consequence, sensory models are often tested by comparing neural responses to natural stimuli with model responses to those stimuli. One challenge is that distinct model features are often correlated across natural stimuli, and thus model features can predict neural responses even if they do not in fact drive them. Here, we propose a simple alternative for testing a sensory model: we synthesize a stimulus that yields the same model response as each of a set of natural stimuli, and test whether the natural and “model-matched” stimuli elicit the same neural responses. We used this approach to test whether a common model of auditory cortex—in which spectrogram-like peripheral input is processed by linear spectrotemporal filters—can explain fMRI responses in humans to natural sounds. Prior studies have that shown that this model has good predictive power throughout auditory cortex, but this finding could reflect feature correlations in natural stimuli. We observed that fMRI responses to natural and model-matched stimuli were nearly equivalent in primary auditory cortex (PAC) but that nonprimary regions, including those selective for music or speech, showed highly divergent responses to the two sound sets. This dissociation between primary and nonprimary regions was less clear from model predictions due to the influence of feature correlations across natural stimuli. Our results provide a signature of hierarchical organization in human auditory cortex, and suggest that nonprimary regions compute higher-order stimulus properties that are not well captured by traditional models. Our methodology enables stronger tests of sensory models and could be broadly applied in other domains.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant BCS-1634050)en_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pbio.2005127en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePLoSen_US
dc.titleNeural responses to natural and model-matched stimuli reveal distinct computations in primary and nonprimary auditory cortexen_US
dc.typeArticleen_US
dc.identifier.citationNorman-Haignere, Sam V., and Josh H. McDermott. “Neural Responses to Natural and Model-Matched Stimuli Reveal Distinct Computations in Primary and Nonprimary Auditory Cortex.” Edited by Matt Davis. PLOS Biology 16, no. 12 (December 3, 2018): e2005127. © 2018 Norman-Haignere, McDermotten_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.mitauthorNorman-Haignere, Samuel Victor
dc.contributor.mitauthorMcDermott, Joshua H.
dc.relation.journalPLOS Biologyen_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.updated2019-02-19T13:52:21Z
dspace.orderedauthorsNorman-Haignere, Sam V.; McDermott, Josh H.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-3965-2503
mit.licensePUBLISHER_CCen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record