Title |
Emotion recognition of static and dynamic faces in autism spectrum disorder
|
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Published in |
Cognition and Emotion, December 2013
|
DOI | 10.1080/02699931.2013.867832 |
Pubmed ID | |
Authors |
Peter G. Enticott, Hayley A. Kennedy, Patrick J. Johnston, Nicole J. Rinehart, Bruce J. Tonge, John R. Taffe, Paul B. Fitzgerald |
Abstract |
There is substantial evidence for facial emotion recognition (FER) deficits in autism spectrum disorder (ASD). The extent of this impairment, however, remains unclear, and there is some suggestion that clinical groups might benefit from the use of dynamic rather than static images. High-functioning individuals with ASD (n = 36) and typically developing controls (n = 36) completed a computerised FER task involving static and dynamic expressions of the six basic emotions. The ASD group showed poorer overall performance in identifying anger and disgust and were disadvantaged by dynamic (relative to static) stimuli when presented with sad expressions. Among both groups, however, dynamic stimuli appeared to improve recognition of anger. This research provides further evidence of specific impairment in the recognition of negative emotions in ASD, but argues against any broad advantages associated with the use of dynamic displays. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Venezuela, Bolivarian Republic of | 1 | 33% |
United States | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | <1% |
Netherlands | 1 | <1% |
Germany | 1 | <1% |
Italy | 1 | <1% |
Unknown | 135 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 26 | 19% |
Student > Ph. D. Student | 25 | 18% |
Researcher | 16 | 12% |
Student > Bachelor | 15 | 11% |
Student > Doctoral Student | 8 | 6% |
Other | 20 | 14% |
Unknown | 29 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 63 | 45% |
Social Sciences | 9 | 6% |
Medicine and Dentistry | 9 | 6% |
Neuroscience | 6 | 4% |
Computer Science | 5 | 4% |
Other | 13 | 9% |
Unknown | 34 | 24% |