Concavity as a diagnostic feature of visual scenes

Annie Cheng, Dirk B. Walther, Soojin Park, Daniel D. Dilks

Research output: Contribution to journalArticlepeer-review

Abstract

Despite over two decades of research on the neural mechanisms underlying human visual scene, or place, processing, it remains unknown what exactly a “scene” is. Intuitively, we are always inside a scene, while interacting with the outside of objects. Hence, we hypothesize that one diagnostic feature of a scene may be concavity, portraying “inside”, and predict that if concavity is a scene-diagnostic feature, then: 1) images that depict concavity, even non-scene images (e.g., the “inside” of an object – or concave object), will be behaviorally categorized as scenes more often than those that depict convexity, and 2) the cortical scene-processing system will respond more to concave images than to convex images. As predicted, participants categorized concave objects as scenes more often than convex objects, and, using functional magnetic resonance imaging (fMRI), two scene-selective cortical regions (the parahippocampal place area, PPA, and the occipital place area, OPA) responded significantly more to concave than convex objects. Surprisingly, we found no behavioral or neural differences between images of concave versus convex buildings. However, in a follow-up experiment, using tightly-controlled images, we unmasked a selective sensitivity to concavity over convexity of scene boundaries (i.e., walls) in PPA and OPA. Furthermore, we found that even highly impoverished line drawings of concave shapes are behaviorally categorized as scenes more often than convex shapes. Together, these results provide converging behavioral and neural evidence that concavity is a diagnostic feature of visual scenes.

Original languageEnglish
Article number117920
JournalNeuroImage
Volume232
DOIs
Publication statusPublished - 2021 May 15

Bibliographical note

Funding Information:
We would like to thank the Facility for Education and Research in Neuroscience (FERN) Imaging Center in the Department of Psychology, Emory University , Atlanta, GA and the F.M. Kirby Research Center for Functional Brain Imaging in the Kennedy Krieger Institute, Johns Hopkins University , Baltimore, MA; Andrew Persichetti, Frederik Kamps, Yaseen Jamal, Jeongho Park, Donald Li, Guldehan Durman and Jeanette Wong for their support and assistance. This work was supported by a National Eye Institute (NEI) grant ( R01EY029724 ) (DDD), an NSERC Discovery Grant ( RGPIN-2015-06696 ) to DBW, and a National Eye Institute (NEI) grant ( R01EY026042 ), National Research Foundation of Korea (NRF) grant (funded by MSIP-2019028919 ) and Yonsei University Future-leading Research Initiative ( 2018-22-0184 ) to SP. The authors declare no competing financial interests.

Publisher Copyright:
© 2021

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

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