English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Human observers can rapidly classify real-world scenes into their natural categories (e.g. beaches, mountains). It is unclear what neural mechanisms underlie this rapid processing of scenes. In a previous behavioral study, we demonstrated that local ribbon symmetry facilitates scene classification. Here we manipulate the ribbon symmetry content of line drawings of real-world scenes and then decode scene categories from patterns of voxel activities of the observers obtained via fMRI. We can decode scene categories from the parahippocampal place area (PPA) more easily from symmetric scenes than asymmetric scenes. In earlier visual areas the decoding accuracy for symmetric and asymmetric scenes was not significantly different. This suggests that the benefit for symmetric scenes in both behavior and fMRI is not solely driven by a lower-level preference for symmetry. Instead, ribbon symmetry may be uniquely informative for scene categorization.

Local contour symmetry facilitates the neural representation of scene categories in the PPA.