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The importance of low spatial frequency information for recognising fearful facial expressions

Publié dansConnection science, vol. 21, no. 1, p. 75-83
Date de publication2009
Résumé

A recent brain imaging study (Vuilleumier, Armony, Driver and Dolan 2003, Nature Neuroscience, 6, 624-631) has shown that amygdala responses to fearful expressions are preferentially driven by intact or low spatial frequency (LSF) images of faces, rather than by high spatial frequency (HSF) images. These results suggest that LSF components processed rapidly via magnocellular pathways within the visual system might be very efficiently conveyed to the amygdala for the rapid recognition of fearful expressions, perhaps via a subcortical pathway that activates the pulvinar and superior colliculus, but which bypasses any finer visual analysis of HSF cues in the striate and temporal extrastriate cortex. The purpose of this paper is to analyse the statistical properties of LSF compared with HSF and intact faces. The statistical analysis shows that the LSF components in faces, which are typically extracted rapidly by the visual system, provide a better source of information than HSF components for the correct categorisation of fearful expressions in faces. These results support the idea that visual pathways from the magnocellular visual neurons might be optimal, at a computational level, for the rapid classification of fearful emotional expressions in human faces.

Mots-clés
  • Connectionist networks
  • Principal component analysis
  • Gabor filters
  • Fearful face recognition
  • Spatial frequencies
Citation (format ISO)
MERMILLOD, Martial et al. The importance of low spatial frequency information for recognising fearful facial expressions. In: Connection science, 2009, vol. 21, n° 1, p. 75–83. doi: 10.1080/09540090802213974
Identifiants
ISSN du journal0954-0091
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Informations techniques

Création24.06.2009 15:05:00
Première validation24.06.2009 15:05:00
Heure de mise à jour14.03.2023 15:09:20
Changement de statut14.03.2023 15:09:20
Dernière indexation15.01.2024 18:36:52
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