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Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. We investigated this by estimating learning rate in environments varying in volatility and uncertainty. Specifically, we correlated autistic traits (in 163 neurotypical participants) with modelled learning behaviour during probabilistic reward learning under the following three conditions: a Stationary Low Noise condition with stable reward contingencies, a Volatile condition with changing reward contingencies and a Stationary High Noise condition where reward probabilities for all options were 60%, resulting in an uncertain, noisy environment. Consistent with earlier findings, we found less optimal decision-making in the Volatile condition for participants with more autistic traits. However, we observed no correlations between underlying adjustments in learning rates and autistic traits, suggesting no impairment in updating learning rates in response to volatile versus noisy environments. Exploratory analyses indicated that impaired performance in the Volatile condition in participants with more autistic traits, was specific to trials with reward contingencies opposite to those initially learned, suggesting a primacy bias. We conclude that performance in volatile environments is lower in participants with more autistic traits, but this cannot be unambiguously attributed to difficulties with adjusting learning rates. Lay abstract Recent theories propose that autism is characterized by an impairment in determining when to learn and when not. Here, we investigated this hypothesis by estimating learning rates (i.e. the speed with which one learns) in three different environments that differed in rule stability and uncertainty. We found that neurotypical participants with more autistic traits performed worse in a volatile environment (with unstable rules), as they chose less often for the most rewarding option. Exploratory analyses indicated that performance was specifically worse when reward rules were opposite to those initially learned for participants with more autistic traits. However, there were no differences in the adjustment of learning rates between participants with more versus less autistic traits. Together, these results suggest that performance in volatile environments is lower in participants with more autistic traits, but that this performance difference cannot be unambiguously explained by an impairment in adjusting learning rates.

A common idea about individuals with autism spectrum disorder (ASD) is that they have an above average preference for predictability and sameness. However, surprisingly little research has gone towards this core symptom, and some studies suggest the preference for predictability in ASD might be less general than commonly assumed. Here, we investigated this important symptom of ASD using three different paradigms, which allowed us to measure preference for predictability under well-controlled experimental conditions. Specifically, we used a dimensional approach by investigating correlations between autistic traits (as measured with the Autism Spectrum Quotient and Social Responsiveness Scale in a neurotypical population) and the scores on three different tasks. The 'music preference' task assessed preferences for tone sequences that varied in predictability. The 'perceptual fluency' task required participants to evaluate stimuli that were preceded by a similar versus dissimilar subliminally presented prime. The 'gambling' task presented four decks of cards that had equal outcome probabilities, but varied in predictability. We observed positive correlations between autistic traits and a preference for predictability in both the music preference and perceptual fluency task. We did not find our hypothesized correlation with gambling behavior, but did observe a post-hoc correlation showing that participants high on autistic traits were faster to choose the predictable deck. Together, these findings show that a relation between autistic traits and preference for predictability can be observed in a standardized lab environment, and should be considered an important first step towards a better, more mechanistic understanding of insistence on sameness in ASD.

Diminished responding to hearing the own name is one of the earliest and strongest predictors of autism spectrum disorder (ASD). Here, we studied for the first time the neural correlates of hearing one's own name in ASD. Based on existing research, we hypothesized enhancement of late parietal positive activity specifically for the own name in neurotypicals, and this effect to be reduced in adults with ASD. Source localization analyses were conducted to estimate group differences in brain regions underlying this effect. 21 adults with ASD, and 21 age-and gender-matched neurotypicals were presented with three categories of names (own name, close other, unknown other) as task-irrelevant deviant stimuli in an auditory oddball paradigm, while EEG was recorded. As expected, a late parietal positivity was observed specifically for own names in neurotypicals, indicating enhanced attention to the own name.This preferential effect was absent in the ASD group. This group difference was associated with diminished activation in the rTPJ in adults with ASD. Further, a familiarity effect was found for the N1, with larger amplitudes for familiar names (own name and close other).However, groups did not differ for this effect. These findings provide evidence of atypical neural responding to hearing one's own name in adults with ASD, suggesting a deficit in selfother distinction, associated with rTPJ dysfunction.Keywords: autism spectrum disorder; ERP; own name; TPJ General Scientific Summary: Infants at risk of ASD are known to show a diminished response to hearing their own name. By investigating the neural response to hearing their own name in adults with ASD, we showed for the first time that also in adulthood, individuals with ASD show an atypical response to hearing their name.3

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