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Real-world scenes are defined by typical part\u2013whole relationships, where the meaning of the whole scene emerges from configurations of localized information present in individual parts of the scene. Such typical part\u2013whole relationships suggest that information from individual scene parts is not processed independently, but that there are mutual influences between the parts and the whole during scene analysis. Here, we review recent research that used a straightforward, but effective approach to study such mutual influences: By dissecting scenes into multiple arbitrary pieces, these studies provide new insights into how the processing of whole scenes is shaped by their constituent parts and, conversely, how the processing of individual parts is determined by their role within the whole scene. We highlight three facets of this research: First, we discuss studies demonstrating that the spatial configuration of multiple scene parts has a profound impact on the neural processing of the whole scene. Second, we review work showing that cortical responses to individual scene parts are shaped by the context in which these parts typically appear within the environment. Third, we discuss studies demonstrating that missing scene parts are interpolated from the surrounding scene context. Bridging these findings, we argue that efficient scene processing relies on an active use of the scene's part\u2013whole structure, where the visual brain matches scene inputs with internal models of what the world should look like.<\/jats:p>","DOI":"10.1162\/jocn_a_01788","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T10:10:16Z","timestamp":1635329416000},"page":"4-15","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":17,"title":["Parts and Wholes in Scene Processing"],"prefix":"10.1162","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9007-3160","authenticated-orcid":true,"given":"Daniel","family":"Kaiser","sequence":"first","affiliation":[{"name":"Justus-Liebig-Universit\u00e4t Gie\u00dfen, Germany"},{"name":"Philipps-Universit\u00e4t Marburg, Germany"},{"name":"University of York, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Radoslaw M.","family":"Cichy","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Germany"},{"name":"Humboldt-Universit\u00e4t zu Berlin, Germany"},{"name":"Bernstein Centre for Computational Neuroscience Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","published-online":{"date-parts":[[2021,12,1]]},"reference":[{"key":"2022040819530169600_bib1","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1146\/annurev.neuro.25.112701.142900","article-title":"Contextual influences on visual processing","volume":"25","author":"Albright","year":"2002","journal-title":"Annual Review of Neuroscience"},{"key":"2022040819530169600_bib2","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.neuroimage.2012.12.023","article-title":"The distributed representation of random and meaningful object pairs in human occipitotemporal cortex: The weighted 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