Adaptive Face Coding Contributes to Individual Differences in Facial Expression Recognition Independently of Affective Factors

Romina Palermo, Linda Roslyn Jeffery, Jessica Faye Lewandowsky, Chiara Fiorentini, Jessica Irons, Amy Dawel, Nichola Sally Burton, Elinor McKone, Gillian Isobel Rhodes

Research output: Contribution to journalArticle

6 Citations (Scopus)
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Abstract

There are large, reliable individual differences in the recognition of facial expressions of emotion across the general population. The sources of this variation are not yet known. We investigated the contribution of a key face perception mechanism, adaptive coding, which calibrates perception to optimize discrimination within the current perceptual “diet.” We expected that a facial expression system that readily recalibrates might boost sensitivity to variation among facial expressions, thereby enhancing recognition ability. We measured adaptive coding strength with an established facial expression aftereffect task and measured facial expression recognition ability with 3 tasks optimized for the assessment of individual differences. As expected, expression recognition ability was positively associated with the strength of facial expression aftereffects. We also asked whether individual variation in affective factors might contribute to expression recognition ability, given that clinical levels of such traits have previously been linked to ability. Expression recognition ability was negatively associated with self-reported anxiety but not with depression, mood, or degree of autism-like or empathetic traits. Finally, we showed that the perceptual factor of adaptive coding contributes to variation in expression recognition ability independently of affective factors.
Original languageEnglish
Pages (from-to)503-517
JournalJournal of Experimental Psychology: Human Perception and Performance
Volume44
Issue number4
Early online date2017
DOIs
Publication statusPublished - Apr 2018

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Facial Expression
Aptitude
Individuality
Autistic Disorder
Recognition (Psychology)
Affective Factors
Individual Differences
Emotions
Anxiety
Depression
Diet
Population

Cite this

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title = "Adaptive Face Coding Contributes to Individual Differences in Facial Expression Recognition Independently of Affective Factors",
abstract = "There are large, reliable individual differences in the recognition of facial expressions of emotion across the general population. The sources of this variation are not yet known. We investigated the contribution of a key face perception mechanism, adaptive coding, which calibrates perception to optimize discrimination within the current perceptual “diet.” We expected that a facial expression system that readily recalibrates might boost sensitivity to variation among facial expressions, thereby enhancing recognition ability. We measured adaptive coding strength with an established facial expression aftereffect task and measured facial expression recognition ability with 3 tasks optimized for the assessment of individual differences. As expected, expression recognition ability was positively associated with the strength of facial expression aftereffects. We also asked whether individual variation in affective factors might contribute to expression recognition ability, given that clinical levels of such traits have previously been linked to ability. Expression recognition ability was negatively associated with self-reported anxiety but not with depression, mood, or degree of autism-like or empathetic traits. Finally, we showed that the perceptual factor of adaptive coding contributes to variation in expression recognition ability independently of affective factors.",
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Adaptive Face Coding Contributes to Individual Differences in Facial Expression Recognition Independently of Affective Factors. / Palermo, Romina ; Jeffery, Linda Roslyn; Lewandowsky, Jessica Faye; Fiorentini, Chiara; Irons, Jessica; Dawel, Amy; Burton, Nichola Sally; McKone, Elinor; Rhodes, Gillian Isobel.

In: Journal of Experimental Psychology: Human Perception and Performance, Vol. 44, No. 4, 04.2018, p. 503-517.

Research output: Contribution to journalArticle

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