Neural Adaptation to Expected Uncertainty in Neurotypical Adults and High-Functioning Adults with Autism Spectrum Disorder
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
The ability to adjust brain resources to manage expected uncertainty is hypothesized to be impaired in autism spectrum disorder (ASD), though the evidence remains limited. To investigate this, we studied 29 neurotypical (NT) and 29 high-functioning adults with ASD performing a probabilistic two-alternative value-based task while undergoing magnetoencephalography (MEG) and pupillometry. The task comprised five sequential blocks with stable reward probabilities (70%:30%), but varying stimulus pairs and reward values, enabling assessment of behavioral and neural adaptation to expected uncertainty. We analyzed a hit rate of advantageous choices, response times, and computational measures of prior belief strength and precision. To examine cortical activation during decision-making, we used MEG source reconstruction to quantify α-β oscillation suppression in decision-relevant cortical regions within the pre-decision time window. Linear mixed models assessed trial-by-trial effects.
Behaviorally, ASD participants exhibited lower overall belief precision but intact probabilistic rule generalization, showing gradual performance improvement and strengthening of prior beliefs across blocks. However, unlike NT individuals, they did not show progressive downscaling of neural activation during decision-making or reduction in neural response to feedback signals as performance improved. Furthermore, on a trial-by-trial basis, increased belief precision in ASD was not associated with reduced cortical activation, a pattern observed in NT individuals.
These findings suggest an atypically rigid and enhanced allocation of neural resources to advantageous decisions in individuals with ASD – although they, as NT individuals, rationally judge such decisions as optimal. This pattern may reflect an aversive response to the irreducible uncertainty inherent in probabilistic decision-making.