Literature DB >> 26431881

My Brain Reads Pain in Your Face, Before Knowing Your Gender.

Claire Czekala1, François Mauguière2, Stéphanie Mazza3, Philip L Jackson4, Maud Frot5.   

Abstract

UNLABELLED: Humans are expert at recognizing facial features whether they are variable (emotions) or unchangeable (gender). Because of its huge communicative value, pain might be detected faster in faces than unchangeable features. Based on this assumption, we aimed to find a presentation time that enables subliminal discrimination of pain facial expression without permitting gender discrimination. For 80 individuals, we compared the time needed (50, 100, 150, or 200 milliseconds) to discriminate masked static pain faces among anger and neutral faces with the time needed to discriminate male from female faces. Whether these discriminations were associated with conscious reportability was tested with confidence measures on 40 other individuals. The results showed that, at 100 milliseconds, 75% of participants discriminated pain above chance level, whereas only 20% of participants discriminated the gender. Moreover, this pain discrimination appeared to be subliminal. This priority of pain over gender might exist because, even if pain faces are complex stimuli encoding both the sensory and the affective component of pain, they signal a danger. This supports the evolution theory relating to the necessity of quickly reading aversive emotions to ensure survival but might also be at the basis of altruistic behavior such as help and compassion. PERSPECTIVE: This study shows that pain facial expression can be processed subliminally after brief presentation times, which might be helpful for critical emergency situations in clinical settings.
Copyright © 2015 American Pain Society. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Masked facial features; area under the receiver operating characteristic curve; pain facial expression; reportability; sensitivity

Mesh:

Year:  2015        PMID: 26431881     DOI: 10.1016/j.jpain.2015.09.006

Source DB:  PubMed          Journal:  J Pain        ISSN: 1526-5900            Impact factor:   5.820


  1 in total

1.  [The AMDS system for the documentation of symptoms and signs associated with pain].

Authors:  Teja W Grömer; Wolfgang Käfferlein; Björn Menger; Ralf Dohrenbusch; Bernd Kappis; Christian Maihöfner; Johannes Kornhuber; Alexandra Philipsen; Helge H O Müller
Journal:  Schmerz       Date:  2017-12       Impact factor: 1.107

  1 in total

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