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Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images
Numerous factors have been reported to underlie the representation of complex images in high-level human visual cortex, including categories (e.g. faces, objects, scenes), animacy, and real-world size, but the extent to which this organization reflects behavioral judgments of real-world stimuli is u...
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Published in: | NeuroImage (Orlando, Fla.) Fla.), 2019-08, Vol.197, p.368-382 |
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description | Numerous factors have been reported to underlie the representation of complex images in high-level human visual cortex, including categories (e.g. faces, objects, scenes), animacy, and real-world size, but the extent to which this organization reflects behavioral judgments of real-world stimuli is unclear. Here, we compared representations derived from explicit behavioral similarity judgments and ultra-high field (7T) fMRI of human visual cortex for multiple exemplars of a diverse set of naturalistic images from 48 object and scene categories. While there was a significant correlation between similarity judgments and fMRI responses, there were striking differences between the two representational spaces. Behavioral judgements primarily revealed a coarse division between man-made (including humans) and natural (including animals) images, with clear groupings of conceptually-related categories (e.g. transportation, animals), while these conceptual groupings were largely absent in the fMRI representations. Instead, fMRI responses primarily seemed to reflect a separation of both human and non-human faces/bodies from all other categories. Further, comparison of the behavioral and fMRI representational spaces with those derived from the layers of a deep neural network (DNN) showed a strong correspondence with behavior in the top-most layer and with fMRI in the mid-level layers. These results suggest a complex relationship between localized responses in high-level visual cortex and behavioral similarity judgments – each domain reflects different properties of the images, and responses in high-level visual cortex may correspond to intermediate stages of processing between basic visual features and the conceptual categories that dominate the behavioral response.
•Different representational spaces for behavioral judgments and fMRI responses.•Strongest correspondence between behavior and fMRI in parahippocampal place area.•Both behavior and fMRI show good correspondence with deep neural network (DNN).•Behavior best correlates with highest DNN layer, fMRI with intermediate DNN layers.•Behavior mainly reflects conceptual properties, fMRI mainly visual properties. |
doi_str_mv | 10.1016/j.neuroimage.2019.04.079 |
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•Different representational spaces for behavioral judgments and fMRI responses.•Strongest correspondence between behavior and fMRI in parahippocampal place area.•Both behavior and fMRI show good correspondence with deep neural network (DNN).•Behavior best correlates with highest DNN layer, fMRI with intermediate DNN layers.•Behavior mainly reflects conceptual properties, fMRI mainly visual properties.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2019.04.079</identifier><identifier>PMID: 31054350</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Behavior ; Brain Mapping ; Female ; Functional magnetic resonance imaging ; Humans ; Information processing ; Judgment - physiology ; Magnetic Resonance Imaging ; Male ; Neural networks ; Pattern Recognition, Visual - physiology ; Photic Stimulation ; Studies ; Visual cortex ; Visual Cortex - physiology ; Young Adult</subject><ispartof>NeuroImage (Orlando, Fla.), 2019-08, Vol.197, p.368-382</ispartof><rights>2019</rights><rights>Published by Elsevier Inc.</rights><rights>Copyright Elsevier Limited Aug 15, 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c507t-e96b9c2c149db0cc683656d3c8e3294da1f59d71113e7ab0a3e0dd7a4183be9d3</citedby><cites>FETCH-LOGICAL-c507t-e96b9c2c149db0cc683656d3c8e3294da1f59d71113e7ab0a3e0dd7a4183be9d3</cites><orcidid>0000-0002-5536-6128 ; 0000-0001-8693-168X ; 0000-0002-8108-1329 ; 0000-0001-8876-933X ; 0000-0001-6861-8964</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31054350$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>King, Marcie L.</creatorcontrib><creatorcontrib>Groen, Iris I.A.</creatorcontrib><creatorcontrib>Steel, Adam</creatorcontrib><creatorcontrib>Kravitz, Dwight J.</creatorcontrib><creatorcontrib>Baker, Chris I.</creatorcontrib><title>Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>Numerous factors have been reported to underlie the representation of complex images in high-level human visual cortex, including categories (e.g. faces, objects, scenes), animacy, and real-world size, but the extent to which this organization reflects behavioral judgments of real-world stimuli is unclear. Here, we compared representations derived from explicit behavioral similarity judgments and ultra-high field (7T) fMRI of human visual cortex for multiple exemplars of a diverse set of naturalistic images from 48 object and scene categories. While there was a significant correlation between similarity judgments and fMRI responses, there were striking differences between the two representational spaces. Behavioral judgements primarily revealed a coarse division between man-made (including humans) and natural (including animals) images, with clear groupings of conceptually-related categories (e.g. transportation, animals), while these conceptual groupings were largely absent in the fMRI representations. Instead, fMRI responses primarily seemed to reflect a separation of both human and non-human faces/bodies from all other categories. Further, comparison of the behavioral and fMRI representational spaces with those derived from the layers of a deep neural network (DNN) showed a strong correspondence with behavior in the top-most layer and with fMRI in the mid-level layers. These results suggest a complex relationship between localized responses in high-level visual cortex and behavioral similarity judgments – each domain reflects different properties of the images, and responses in high-level visual cortex may correspond to intermediate stages of processing between basic visual features and the conceptual categories that dominate the behavioral response.
•Different representational spaces for behavioral judgments and fMRI responses.•Strongest correspondence between behavior and fMRI in parahippocampal place area.•Both behavior and fMRI show good correspondence with deep neural network (DNN).•Behavior best correlates with highest DNN layer, fMRI with intermediate DNN layers.•Behavior mainly reflects conceptual properties, fMRI mainly visual properties.</description><subject>Adult</subject><subject>Behavior</subject><subject>Brain Mapping</subject><subject>Female</subject><subject>Functional magnetic resonance imaging</subject><subject>Humans</subject><subject>Information processing</subject><subject>Judgment - physiology</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Neural networks</subject><subject>Pattern Recognition, Visual - physiology</subject><subject>Photic Stimulation</subject><subject>Studies</subject><subject>Visual cortex</subject><subject>Visual Cortex - physiology</subject><subject>Young Adult</subject><issn>1053-8119</issn><issn>1095-9572</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqFUcuO1DAQtBCIXQZ-AVniwiXBjp2HL0iw4iWtxAE4W47dGRwldrCTkfYD-G86zLI8LpzcUlWXq7oIoZyVnPHmxVgG2FL0szlCWTGuSiZL1qp75JIzVReqbqv7-1yLouNcXZBHOY-MMcVl95BcCESkqNkl-f7Jz34yya83dNzccYawZmqCozam1Vsz0ZPPGz4J8hJDhozTMIFdqfPDAAkX6JLiAkhHMA409uMO7yLZQgBqzQrHmHbYBxrMuiUz-Yzy9GeE_Jg8GMyU4cnteyBf3r75fPW-uP747sPVq-vC1qxdC1BNr2xluVSuZ9Y2nWjqxgnbgaiUdIYPtXIt51xAa3pmBDDnWiN5J3pQThzIy7PusvUzODS3ohO9JLSRbnQ0Xv-NBP9VH-NJN7XCw0oUeH4rkOK3DfKqZ48Zp8kEiFvWVVWpSrKmaZD67B_qGLcUMB6ypMS2GNo6kO7MsinmjJe9M8OZ3rvWo_7dtd671kxq3MbVp3-GuVv8VS4SXp8JgCc9eUg6Ww_BgvMJC9Iu-v__8gMgv8Ta</recordid><startdate>20190815</startdate><enddate>20190815</enddate><creator>King, Marcie L.</creator><creator>Groen, Iris I.A.</creator><creator>Steel, Adam</creator><creator>Kravitz, Dwight J.</creator><creator>Baker, Chris I.</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-5536-6128</orcidid><orcidid>https://orcid.org/0000-0001-8693-168X</orcidid><orcidid>https://orcid.org/0000-0002-8108-1329</orcidid><orcidid>https://orcid.org/0000-0001-8876-933X</orcidid><orcidid>https://orcid.org/0000-0001-6861-8964</orcidid></search><sort><creationdate>20190815</creationdate><title>Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images</title><author>King, Marcie L. ; 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Here, we compared representations derived from explicit behavioral similarity judgments and ultra-high field (7T) fMRI of human visual cortex for multiple exemplars of a diverse set of naturalistic images from 48 object and scene categories. While there was a significant correlation between similarity judgments and fMRI responses, there were striking differences between the two representational spaces. Behavioral judgements primarily revealed a coarse division between man-made (including humans) and natural (including animals) images, with clear groupings of conceptually-related categories (e.g. transportation, animals), while these conceptual groupings were largely absent in the fMRI representations. Instead, fMRI responses primarily seemed to reflect a separation of both human and non-human faces/bodies from all other categories. Further, comparison of the behavioral and fMRI representational spaces with those derived from the layers of a deep neural network (DNN) showed a strong correspondence with behavior in the top-most layer and with fMRI in the mid-level layers. These results suggest a complex relationship between localized responses in high-level visual cortex and behavioral similarity judgments – each domain reflects different properties of the images, and responses in high-level visual cortex may correspond to intermediate stages of processing between basic visual features and the conceptual categories that dominate the behavioral response.
•Different representational spaces for behavioral judgments and fMRI responses.•Strongest correspondence between behavior and fMRI in parahippocampal place area.•Both behavior and fMRI show good correspondence with deep neural network (DNN).•Behavior best correlates with highest DNN layer, fMRI with intermediate DNN layers.•Behavior mainly reflects conceptual properties, fMRI mainly visual properties.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>31054350</pmid><doi>10.1016/j.neuroimage.2019.04.079</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-5536-6128</orcidid><orcidid>https://orcid.org/0000-0001-8693-168X</orcidid><orcidid>https://orcid.org/0000-0002-8108-1329</orcidid><orcidid>https://orcid.org/0000-0001-8876-933X</orcidid><orcidid>https://orcid.org/0000-0001-6861-8964</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Behavior Brain Mapping Female Functional magnetic resonance imaging Humans Information processing Judgment - physiology Magnetic Resonance Imaging Male Neural networks Pattern Recognition, Visual - physiology Photic Stimulation Studies Visual cortex Visual Cortex - physiology Young Adult |
title | Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images |
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