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Facial Emotions Improve Face Discrimination Learning

Lorenzino, Martina
•
Caudek, Corrado
2014
  • Controlled Vocabulary...

Abstract
How visual experience modulates the ability to discriminate faces from one another is still poorly understood. The aim of this study is to investigate whether emotions may favor face discrimination learning. To this purpose, we measured face discrimination thresholds before and after a training phase, where participants are exposed to (task-irrelevant) subtle variations in face images from trial to trial. A task-irrelevant perceptual learning paradigm was used because it closely mimics the learning processes that daily occur, without a conscious intention to learn and without a focused attention on specific facial features. During the four sessions of training, participants performed a contrast-discrimination task on face images. The task-irrelevant features were face images variations along the morphing continuum of facial identity (Identity group) or face images variations along the morphing continuum of emotional expressions (Emotion group). A group of participants (Control group) did not perform the contrast training, but their face discrimination thresholds were measured with the same temporal gap between them as the other two groups. Results indicate a face discrimination improvement only for the Emotion group. Participants in the Emotion Group showed a discrimination improvement when tested with variations along the dimension of identity and with variations along the dimension of expression, even if identity variations were not used during training. The present results suggest a role of emotions in face discrimination learning and show that faces, differently from the other classes of stimuli, may manifest a higher degree of learning transfer.
Archivio
http://hdl.handle.net/10077/10517
Diritti
open access
Soggetti
  • Face discrimination

  • Task-irrelevant perce...

  • Emotions

  • Contrast discriminati...

Visualizzazioni
2
Data di acquisizione
Apr 19, 2024
Vedi dettagli
google-scholar
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