Insomniacs misidentify angry faces as fearful faces because of missing the eyes: An eye-tracking study

Jinxiao ZHANG, Antoni B. CHAN, Esther Yuet Ying LAU, Janet H. HSIAO

Research output: Contribution to conferencePapers

Abstract

Insomniacs were found to have compromised perception of facial expressions. Through eye movement examinations, here we test the hypothesis that this effect is due to impaired visual attention functions for retrieving diagnostic features in facial expression judgments. 23 individuals with insomnia symptoms and 23 non-insomniac controls completed a task to categorize happy, sad, fearful, and angry faces. The insomniacs were less accurate to recognize angry faces and made more “fearful” mistakes than controls. A hidden Markov modeling approach for eye movement data analysis revealed that when recognizing angry faces, more insomniacs adopted an eye movement pattern focusing on the mouth while more controls adopted a pattern attending to both the eyes and the mouth. This result is consistent with previous findings that the primary diagnostic feature for recognizing angry faces is the eyes suggesting that impaired information selection through visual attention control may account for the compromised emotion perception in insomniac individuals.
Original languageEnglish
Publication statusPublished - Jul 2017
Event39th Annual Meeting of the Cognitive Science Society (CogSci 2017): Computational Foundations of Cognition - London, United Kingdom
Duration: 26 Jul 201729 Jul 2017

Conference

Conference39th Annual Meeting of the Cognitive Science Society (CogSci 2017): Computational Foundations of Cognition
Abbreviated titleCogSci 2017
Country/TerritoryUnited Kingdom
CityLondon
Period26/07/1729/07/17

Citation

Zhang, J., Chan, A. B., Lau, E. Y. Y., & Hsiao, J. H. (2017, July). Insomniacs misidentify angry faces as fearful faces because of missing the eyes: An eye-tracking study. Paper presented at the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017), Hilton London Metropole, London, UK.

Keywords

  • Insomnia
  • Eye-tracking
  • Hidden Markov model
  • Facial expression

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