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Recognition of facial emotion in low vision: A flexible usage of facial features

Published online by Cambridge University Press:  01 July 2008

MURIEL BOUCART*
Affiliation:
Lab. Neuroscience Fonctionnelle et Pathologies, Université Lille 2, CNRS, Lille, France
JEAN-FRANÇOIS DINON
Affiliation:
Lab. Neuroscience Fonctionnelle et Pathologies, Université Lille 2, CNRS, Lille, France
PASCAL DESPRETZ
Affiliation:
Lab. Neuroscience Fonctionnelle et Pathologies, Université Lille 2, CNRS, Lille, France
THOMAS DESMETTRE
Affiliation:
Centre d'Imagerie, de Laser et de Réadaptation Basse Vision, Lambersart, France
KATRINE HLADIUK
Affiliation:
Centre d'Imagerie, de Laser et de Réadaptation Basse Vision, Lambersart, France
AUDE OLIVA
Affiliation:
Department of Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts
*
*Address correspondence and reprint requests to: Muriel Boucart, CHRU Lille, Hôpital Roger Salengro, service EFV, Lab. Neurosciences Fonctionnelles & Pathologies CNRS (UMR 8160), 59037 Lille, France. E-mail: [email protected]

Abstract

Age-related macular degeneration (AMD) is a major cause of visual impairment in people older than 50 years in Western countries, affecting essential tasks such as reading and face recognition. Here we investigated the mechanisms underlying the deficit in recognition of facial expressions in an AMD population with low vision. Pictures of faces displaying different emotions with the mouth open or closed were centrally displayed for 300 ms. Participants with AMD with low acuity (mean 20/200) and normally sighted age-matched controls performed one of two emotion tasks: detecting whether a face had an expression or not (expressive/non expressive (EXNEX) task) or categorizing the facial emotion as happy, angry, or neutral (categorization of expression (CATEX) task). Previous research has shown that healthy observers are mainly using high spatial frequencies in an EXNEX task while performance at a CATEX task was preferentially based on low spatial frequencies. Due to impaired processing of high spatial frequencies in central vision, we expected and observed that AMD participants failed at deciding whether a face was expressive or not but categorized normally the emotion of the face (e.g., happy, angry, neutral). Moreover, we observed that AMD participants mostly identified emotions using the lower part of the face (mouth). Accuracy did not differ between the two tasks for normally sighted observers. The results indicate that AMD participants are able to identify facial emotion but must base their decision mainly on the low spatial frequencies, as they lack the perception of finer details.

Type
Research Articles
Copyright
Copyright © Cambridge University Press 2008

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