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Duncan Rowland

Researcher at University of Lincoln

Publications -  67
Citations -  8976

Duncan Rowland is an academic researcher from University of Lincoln. The author has contributed to research in topics: Facial expression & Documentation. The author has an hindex of 28, co-authored 67 publications receiving 8677 citations. Previous affiliations of Duncan Rowland include University of London & University of St Andrews.

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A differential neural response in the human amygdala to fearful and happy facial expressions

TL;DR: Direct in vivo evidence of a differential neural response in the human amygdala to facial expressions of fear and happiness is reported, providing direct evidence that the humangdala is engaged in processing the emotional salience of faces, with a specificity of response to fearful facial expressions.
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A specific neural substrate for perceiving facial expressions of disgust

TL;DR: Functional magnetic resonance imaging was used to examine the neural substrate for perceiving disgust expressions and found the neural response to facial expressions of disgust in others is thus closely related to appraisal of distasteful stimuli.
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Effects of sexual dimorphism on facial attractiveness

TL;DR: The results of asking subjects to choose the most attractive faces from continua that enhanced or diminished differences between the average shape of female and male faces indicate a selection pressure that limits sexual dimorphism and encourages neoteny in humans.
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Symmetry and human facial attractiveness.

TL;DR: For example, this article found that increasing symmetry of face shape increases ratings of attractiveness for both male and female faces, which suggests facial symmetry may have a positive impact on mate selection in humans.
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Facial expression megamix: Tests of dimensional and category accounts of emotion recognition

TL;DR: Four experiments investigating the perception of photographic quality continua of interpolated ('morphed') facial expressions derived from prototypes of the 6 emotions in the Ekman and Friesen series suggest that rapid classification of prototypes and better across boundary discriminability reflect the underlying organisation of human categorisation abilities.