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Cortical networks of dynamic scene category representation in the human brain

Çelik, Emin and Keles, Umit and Kiremitçi, İbrahim and Gallant, Jack L. and Çukura, Tolga (2021) Cortical networks of dynamic scene category representation in the human brain. Cortex, 143 . pp. 127-147. ISSN 0010-9452. doi:10.1016/j.cortex.2021.07.008.

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Humans have an impressive ability to rapidly process global information in natural scenes to infer their category. Yet, it remains unclear whether and how scene categories observed dynamically in the natural world are represented in cerebral cortex beyond few canonical scene-selective areas. To address this question, here we examined the representation of dynamic visual scenes by recording whole-brain blood oxygenation level-dependent (BOLD) responses while subjects viewed natural movies. We fit voxelwise encoding models to estimate tuning for scene categories that reflect statistical ensembles of objects and actions in the natural world. We find that this scene-category model explains a significant portion of the response variance broadly across cerebral cortex. Cluster analysis of scene-category tuning profiles across cortex reveals nine spatially-segregated networks of brain regions consistently across subjects. These networks show heterogeneous tuning for a diverse set of dynamic scene categories related to navigation, human activity, social interaction, civilization, natural environment, non-human animals, motion-energy, and texture, suggesting that the organization of scene category representation is quite complex.

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Additional Information:© 2021 Elsevier Ltd. Received 22 September 2020, Revised 28 June 2021, Accepted 14 July 2021, Available online 24 July 2021. Reviewed 27 May 2021; Action editor Ana B. Chica. The authors declare no competing financial interests. The work was supported in part by a National Eye Institute Grant (EY019684), by a Marie Curie Actions Career Integration Grant (PCIG13-GA-2013-618101), by a European Molecular Biology Organization Installation Grant (IG 3028), by a TUBA GEBIP 2015 fellowship, and by a Science Academy BAGEP 2017 award. We thank D. Stansbury, A. Huth, and S. Nishimoto for assistance in various aspects of this research. We report how we determined our sample size, all data exclusions, all inclusion/exclusion criteria, whether inclusion/exclusion criteria were established prior to data analysis, all manipulations, and all measures in the study. No part of the study procedures or analyses was pre-registered prior to the research being conducted. CRediT author statement: Emin Çelik: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing – Review & Editing, Visualization. Umit Keles: Conceptualization, Methodology, Software, Formal analysis, Writing – Original Draft, Visualization. İbrahim Kiremitçi: Validation, Formal analysis. Jack L. Gallant: Writing – Review & Editing. Tolga Çukur: Conceptualization, Investigation, Resources, Writing – Review & Editing, Supervision, Project Administration, Funding Acquisition. Open practices: The study in this article earned Open Data and Open Materials badges for transparent practices. Data for this study can be found at and
Funding AgencyGrant Number
Marie Curie Fellowship618101
European Molecular Biology Organization (EMBO)IG 3028
TÜBA-Üstün Başarılı Genç Bilim İnsanı Ödülleri (GEBİP)UNSPECIFIED
Science AcademyUNSPECIFIED
Subject Keywords:fMRI; Dynamic scene category representation; Voxelwise encoding model; Cluster analysis
Record Number:CaltechAUTHORS:20210817-160947887
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Official Citation:Emin Çelik, Umit Keles, İbrahim Kiremitçi, Jack L. Gallant, Tolga Çukur, Cortical networks of dynamic scene category representation in the human brain, Cortex, Volume 143, 2021, Pages 127-147, ISSN 0010-9452,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110290
Deposited By: Tony Diaz
Deposited On:18 Aug 2021 21:59
Last Modified:18 Aug 2021 21:59

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