Electrophysiological correlates of emotional face processing in typically developing adults and adults with high functioning Autism

Emotional expressions have been found to affect various event-related potentials (ERPs). Furthermore, socio-emotional functioning is altered in individuals with autism, and a growing body of neuroimaging and electrophysiological evidence substantiates underlying neural differences for face processing in this population. However, relatively few studies have examined the time-course of emotional face processing in autism. This study examined how implicit (not the intended focus of attention) versus explicit (the intended focus of attention) presentations of emotion differentially influenced the processing of fearful, sad, and happy facial expressions relative to neutral expressions. Study 1 was conducted in a sample of typically developing (TD) young adults. Study 2 compared a group of high-functioning young adults with autism to a new group of age-, gender-, and IQ-matched TD controls. Results from both studies supported the prediction that ERP components would be differently modulated as a function of emotion relevance and emotional expression, suggesting different emotions and implicit/explicit presentations are processed in partially separable neural networks. Both studies found that sad faces uniquely modulated the P150, VPP, EAP, and LPP in TD adults. This unique response to sad faces was found as early as 150ms post-stimulus onset over frontal electrodes, suggesting early, relatively automatic recognition of sad faces. It was also found over posterior sites as indexed by the LPP, reflecting more conscious appraisal of the emotion. In individuals with autism, sad faces did not elicit distinctive effects. Rather, happy faces uniquely modulated the P150 and N4a, suggesting that this positive social emotion was most salient to adults with autism whereas sad faces, which may communicate a social error message and elicit empathy, were most salient to TD adults. Both experiments provide support for a neural network that is sensitive to socially relevant information and provide important clues for underlying neural differences that may contribute to difficulties with socio-emotional functioning so commonly reported in autism.