BackgroundPrevious research has found accumulating evidence for atypical reward processing in autism spectrum disorders (ASD), particularly in the context of social rewards. Yet, this line of research has focused largely on positive social reinforcement, while little is known about the processing of negative reinforcement in individuals with ASD.MethodsThe present study examined neural responses to social negative reinforcement (a face displaying negative affect) and non-social negative reinforcement (monetary loss) in children with ASD relative to typically developing children, using functional magnetic resonance imaging (fMRI).ResultsWe found that children with ASD demonstrated hypoactivation of the right caudate nucleus while anticipating non-social negative reinforcement and hypoactivation of a network of frontostriatal regions (including the nucleus accumbens, caudate nucleus, and putamen) while anticipating social negative reinforcement. In addition, activation of the right caudate nucleus during non-social negative reinforcement was associated with individual differences in social motivation.ConclusionsThese results suggest that atypical responding to negative reinforcement in children with ASD may contribute to social motivational deficits in this population.

An econometric choice task was used to estimate the implicit reward value of social and non-social stimuli related to restricted interests in children and adolescents with (n = 12) and without (n = 22) autism spectrum disorder (ASD). Mixed effects logistic regression analyses revealed that groups differed in valuation of images related to restricted interests: control children were indifferent to cash payouts to view these images, but children with ASD were willing to receive less cash payout to view these images. Groups did not differ in valuation of social images or non-social images not related to restricted interests. Results highlight that motivational accounts of ASD should also consider the reward value of non-social stimuli related to restricted interests in ASD (Dichter and Adolphs, 2012).

We examined the late positive potential (LPP) event related potential in response to social and nonsocial stimuli from 9-19 years old youth with (n = 35) and without (n = 34) ASD. Social stimuli were faces with positive expressions and nonsocial stimuli were related to common restricted interests in ASD (e.g., electronics, vehicles, etc.). The ASD group demonstrated relatively smaller LPP amplitude to social stimuli and relatively larger LPP amplitude to nonsocial stimuli. There were no group differences in subjective ratings of images, and there were no significant correlations between LPP amplitude and ASD symptom severity within the ASD group. LPP results suggest blunted motivational responses to social stimuli and heightened motivational responses to nonsocial stimuli in youth with ASD.

Background Experience sampling is a powerful method for obtaining ecologically valid data from research participants in real-world contexts. Given the urgent need for innovative and sensitive outcome measures in autism spectrum disorder (ASD) research, the present study sought to examine the feasibility of using experience sampling of positive affect and behavior in adolescents with ASD. Method Nineteen high functioning adolescents with ASD and 20 sex and age matched controls completed smartphone- and Qualtrics® -based experience sampling of positive affect and behavior six times over four days. Results Adherence was excellent: adolescents with ASD completed 85% of the assessments, compared to 93% in controls, and response rates were not impacted by age or IQ. Groups did not differ in positive affect overall or as a function of activities, nor did groups differ in the proportion of assessments completed during social or nonsocial activities. However, groups did differ in the proportion of assessments completed during preferred activities. Conclusions Results suggest that smartphone- and Qualtrics® -based experience sampling with high functioning adolescents with ASD is feasible and captures real-world behaviors that would not be possible using laboratory-based measures.