September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Exploring a new method to improve facial emotion recognition
Author Affiliations
  • Carlijn van den Boomen
    Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The NetherlandsDepartment of Developmental Psychology, Utrecht University, Utrecht, The Netherlands
  • Sjoerd Stuit
    Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
  • Chantal Kemner
    Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The NetherlandsDepartment of Developmental Psychology, Utrecht University, Utrecht, The Netherlands
Journal of Vision September 2018, Vol.18, 275. doi:10.1167/18.10.275
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      Carlijn van den Boomen, Sjoerd Stuit, Chantal Kemner; Exploring a new method to improve facial emotion recognition. Journal of Vision 2018;18(10):275. doi: 10.1167/18.10.275.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Recognizing emotional expressions is crucial for social interaction. However, individuals can differ greatly in this ability, and those with impairments are known to experience problems in interaction. Difficulties with recognizing emotional expressions may relate to differences in sensitivity to basic visual features. That is, emotional expressions differ in their basic feature-content, for example their contrast energy in specific spatial frequencies and orientations. Importantly, many studies revealed that feature sensitivity can be improved through repeated exposure. Unknown is whether this affects sensitivity for more complex stimuli such as emotional faces. Therefore, we explored the possibility that increasing sensitivity to the basic features that differentiate emotional expressions generalizes to improved facial emotion recognition. In the current experiment, thirty healthy adults participated in a pre-post visual perceptual learning paradigm. During three training sessions, they performed a contrast detection task on a circular noise patch containing the spatial frequency and orientation information that differentiates sad from neutral faces. Note that the noise patches contained no structural information of faces. Both before and after training, detection thresholds were estimated for the training-image and two control images (noise patches based on the feature content that differentiate disgusted and happy faces from neutral faces). Moreover, participants performed an emotion recognition task on sad, disgusted, and happy faces. Results showed increased contrast sensitivity for the noise patches both during and after the training sessions. With respect to generalization to emotion recognition, we show an overall decrease in detection thresholds. However, the decrease was not specific to the trained emotion. Still, emotion recognition performance for sad faces showed a significant correlation to the decrease in contrast thresholds. Overall, this study provides the first indication that training the sensitivity for the basic features that differentiate emotional expressions generalizes to emotional expression recognition.

Meeting abstract presented at VSS 2018

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