A robust method for measuring an individual's sensitivity to facial expressions.

This paper describes a method to measure the sensitivity of an individual to different facial expressions. 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. Sensitivity is measured by asking participants to discriminate between an emotional facial expression and a neutral expression of the same face. The expression was diluted to different degrees by combining it in different proportions with the neutral expression using morphing software. 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. Individuals could reliably discriminate happy expressions diluted with a greater proportion of the neutral expression compared with that required for discrimination of fearful expressions. This tells us that individual participants are more sensitive to happy compared with fearful expressions. 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. Increased sensitivity to happy compared with fear expressions was affected at smaller image sizes for some 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.