Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021)

John M Henderson; Taylor R Hayes; Candace E Peacock; Gwendolyn Rehrig

doi:10.1016/j.cognition.2021.104742

Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021)

Cognition. 2021 Sep:214:104742. doi: 10.1016/j.cognition.2021.104742. Epub 2021 Apr 21.

Authors

John M Henderson¹, Taylor R Hayes², Candace E Peacock³, Gwendolyn Rehrig⁴

Affiliations

¹ Center for Mind and Brain, University of California, Davis, USA; Department of Psychology, University of California, Davis, USA. Electronic address: johnhenderson@ucdavis.edu.
² Center for Mind and Brain, University of California, Davis, USA.
³ Center for Mind and Brain, University of California, Davis, USA; Department of Psychology, University of California, Davis, USA.
⁴ Department of Psychology, University of California, Davis, USA.

PMID: 33892912
DOI: 10.1016/j.cognition.2021.104742

Abstract

Pedziwiatr, Kümmerer, Wallis, Bethge, & Teufel (2021) contend that Meaning Maps do not represent the spatial distribution of semantic features in scenes. We argue that Pesziwiatr et al. provide neither logical nor empirical support for that claim, and we conclude that Meaning Maps do what they were designed to do: represent the spatial distribution of meaning in scenes.

Keywords: Attention; Eye movements; Scene perception.

Publication types

Research Support, N.I.H., Extramural
Comment

MeSH terms

Attention
Eye Movements
Fixation, Ocular*
Humans
Semantics*
Visual Perception