Literature DB >> 26075962

The role of spatial frequency information in the recognition of facial expressions of pain.

Shan Wang1, Christopher Eccleston, Edmund Keogh.   

Abstract

Being able to detect pain from facial expressions is critical for pain communication. Alongside identifying the specific facial codes used in pain recognition, there are other types of more basic perceptual features, such as spatial frequency (SF), which refers to the amount of detail in a visual display. Low SF carries coarse information, which can be seen from a distance, and high SF carries fine-detailed information that can only be perceived when viewed close up. As this type of basic information has not been considered in the recognition of pain, we therefore investigated the role of low-SF and high-SF information in the decoding of facial expressions of pain. Sixty-four pain-free adults completed 2 independent tasks: a multiple expression identification task of pain and core emotional expressions and a dual expression "either-or" task (pain vs fear, pain vs happiness). Although both low-SF and high-SF information make the recognition of pain expressions possible, low-SF information seemed to play a more prominent role. This general low-SF bias would seem an advantageous way of potential threat detection, as facial displays will be degraded if viewed from a distance or in peripheral vision. One exception was found, however, in the "pain-fear" task, where responses were not affected by SF type. Together, this not only indicates a flexible role for SF information that depends on task parameters (goal context) but also suggests that in challenging visual conditions, we perceive an overall affective quality of pain expressions rather than detailed facial features.

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Year:  2015        PMID: 26075962     DOI: 10.1097/j.pain.0000000000000226

Source DB:  PubMed          Journal:  Pain        ISSN: 0304-3959            Impact factor:   6.961


  3 in total

1.  Modulating adaptation to emotional faces by spatial frequency filtering.

Authors:  Giulia Prete; Bruno Laeng; Luca Tommasi
Journal:  Psychol Res       Date:  2016-11-26

2.  The Predictive Role of Low Spatial Frequencies in Automatic Face Processing: A Visual Mismatch Negativity Investigation.

Authors:  Adeline Lacroix; Sylvain Harquel; Martial Mermillod; Laurent Vercueil; David Alleysson; Frédéric Dutheil; Klara Kovarski; Marie Gomot
Journal:  Front Hum Neurosci       Date:  2022-03-11       Impact factor: 3.169

3.  The role of spatial frequencies for facial pain categorization.

Authors:  Isabelle Charbonneau; Joël Guérette; Stéphanie Cormier; Caroline Blais; Guillaume Lalonde-Beaudoin; Fraser W Smith; Daniel Fiset
Journal:  Sci Rep       Date:  2021-07-13       Impact factor: 4.379

  3 in total

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