Relationship between low mood and micro-expression processing: Evidence of negative bias in interpreting fleeting facial expressions

Kasia Wezowski*, Ian S. Penton-Voak

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Depression affects the recognition of emotion in facial expressions by reducing the detection accuracy and adding a bias towards negativity. However, no study has examined associations between depression and the recognition of microfacial expressions (fleeting facial cues of emotions in people's faces). Thus, we investigated associations between low mood and micro-expression processing using video stimuli of micro-expressions. We examined whether (i) individuals with low mood had trouble recognizing emotions, (ii) were more likely to perceive happy facial expressions as neutral and neutral facial expressions as sad, and (iii) recognized sad emotional expressions better than control subjects (n = 349). We found that participants with low mood showed poorer performance when judging emotions in faces (p = 0.03). Furthermore, there was a specific deficit among them in recognizing happiness. Lastly, participants with low moods were more likely to perceive neutral faces as sad (p = 0.042). However, no evidence was found that individuals with low moods confused happy faces as neutral or were better than the control group at recognizing sad faces. Our results show that mood affects the perception of emotions in facial expressions, which has the potential to negatively affect interpersonal interactions and ultimately quality of life.
Original languageEnglish
Article number231944
Number of pages13
JournalRoyal Society Open Science
Volume11
Issue number7
DOIs
Publication statusPublished - 31 Jul 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

Keywords

  • depression
  • facial expression
  • micro-expression recognition

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