Spatial and feature-based attention to expressive faces

Kestutis Kveraga, David De Vito, Cody Cushing, Hee Yeon Im, Daniel N. Albohn, Reginald B. Adams

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Facial emotion is an important cue for deciding whether an individual is potentially helpful or harmful. However, facial expressions are inherently ambiguous and observers typically employ other cues to categorize emotion expressed on the face, such as race, sex, and context. Here, we explored the effect of increasing or reducing different types of uncertainty associated with a facial expression that is to be categorized. On each trial, observers responded according to the emotion and location of a peripherally presented face stimulus and were provided with either: (1) no information about the upcoming face; (2) its location; (3) its expressed emotion; or (4) both its location and emotion. While cueing emotion or location resulted in faster response times than cueing unpredictive information, cueing face emotion alone resulted in faster responses than cueing face location alone. Moreover, cueing both stimulus location and emotion resulted in a superadditive reduction of response times compared with cueing location or emotion alone, suggesting that feature-based attention to emotion and spatially selective attention interact to facilitate perception of face stimuli. While categorization of facial expressions was significantly affected by stable identity cues (sex and race) in the face, we found that these interactions were eliminated when uncertainty about facial expression, but not spatial uncertainty about stimulus location, was reduced by predictive cueing. This demonstrates that feature-based attention to facial expression greatly attenuates the need to rely on stable identity cues to interpret facial emotion.

Original languageEnglish (US)
Pages (from-to)967-975
Number of pages9
JournalExperimental Brain Research
Volume237
Issue number4
DOIs
StatePublished - Apr 8 2019

All Science Journal Classification (ASJC) codes

  • General Neuroscience

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