![]() ![]() The model-comparison approach tests the hypothesis that differences between the psychometric functions fit to an individual’s performance with happy and fear expressions are real rather than due to sampling error. This paper goes further to show how the model-comparison approach (Prins & Kingdom, 2018) can be used to test for significant differences in the sensitivity of the individual to two different facial expressions (happy and fear). Dynamic morphed stimuli have also been used to identify the intensity at which an expression is detectable or able to be categorized (Fiorentini, Schmidt, & Viviani, 2012 Fiorentini & Viviani, 2011 Niedenthal, Brauer, Halberstadt, & Innes-Ker, 2001 Niedenthal, Halberstadt, Margolin, & Innes-Ker, 2000). Positive correlations between degree of morphing and intensity rating (Calder, Rowland, et al., 2000b) and accuracy recognizing emotions (Hess, Blairy, & Kleck, 1997) have been found for static faces. Such stimuli are arguably more ecologically valid as emotions expressed in everyday life vary in their intensity. Images at intermediary stages are saved creating new images of expressions with intermediate intensities. ![]() Computer software is used to morph between a neutral face and a face of the same individual with a full expression. In addition to studies using faces with fully formed expressions (full intensity), morphing techniques have been used to generate face stimuli with varying intensities of expression. ![]() This paper presents a way to measure the sensitivity of an individual to different facial expressions and therefore identify perceptually equivalent stimuli tailored to individuals. Comparing performance with and without perceptually equivalent stimuli could provide greater insight into the relative contribution of perceptual and affective processing in facial emotion recognition tasks. Using perceptually equivalent stimuli in a different paradigm (e.g., categorial emotion recognition task) would reduce the contribution of the salience of the visual signals (perceptual processing) and amplify the relative contribution of affective processing. Tailoring the stimuli to individual participants would influence the relative contribution of perceptual and affective processing in the paradigm. Such perceptually equivalent stimuli could then be used in another experimental paradigm to measure the effect of affect on performance. Measures of sensitivity to different expressions could be used to identify stimuli from different affective categories (e.g., happy and fear) that individual participants find equally challenging to discriminate (perceptually equivalent). Dissociating the effect of perceptual processing from affective processing in facial expression recognition might be achieved by using stimuli that are tailored to individual participants. ![]() Application of the approach for use with clinical populations, as well as understanding the relative contribution of perceptual processing and affective processing in facial expression recognition, is discussed.įacial emotion recognition relies on both perceptual processing and processing of affect from nonsensory systems, the relative contribution of which remains unclear (see Calvo & Nummenmaa, 2016, for a review). Increased sensitivity to happy compared with fear expressions was affected at smaller image sizes for some participants. Sensitivity is equivalent when measured on two different testing sessions, and greater sensitivity to happy expressions is maintained with short stimulus durations and stimuli generated using different morphing software. This tells us that individual participants are more sensitive to happy compared with fearful expressions. Individuals could reliably discriminate happy expressions diluted with a greater proportion of the neutral expression compared with that required for discrimination of fearful expressions. Sensitivity is defined as measurement of the proportion of neutral expression in a stimulus required for participants to discriminate the emotional expression on 75% of presentations. The expression was diluted to different degrees by combining it in different proportions with the neutral expression using morphing software. Sensitivity is measured by asking participants to discriminate between an emotional facial expression and a neutral expression of the same face. It shows that individual participants are more sensitive to happy than to fearful expressions and that the differences are statistically significant using the model-comparison approach. This paper describes a method to measure the sensitivity of an individual to different facial expressions. ![]()
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