Cognitive and social alterations characterize Autism Spectrum Disorder (ASD), yet
comprehensive explanations are challenged by ASD’s heterogeneity. One candidate framework
is predictive processing, which posits that predictive processes are altered in ASD
(e.g., slower internal model updating). We tested this framework using the spectrum
approach, which suggests that subclinical autistic traits are continuously distributed
in the general population, with most diagnosed individuals above a threshold. We recruited
neurotypical adults ( N = 296) to examine the relationship between autistic traits
and predictive processing. Using an implicit statistical learning task, we tested
model updating in an unsupervised, ecologically valid manner, and assessed speed/accuracy
trade-off to control for potential visuomotor performance confounds in ASD. We found
no difference in model updating rate along autistic traits, suggesting no relationship
between these traits and model updating in the general population, contrary to the
slow updating hypothesis. However, our results reveal a difference in the evolution
of speed/accuracy trade-off along the degree of autistic traits, potentially indicating
a shift in the balance of goal-directed and habitual systems related to autistic traits.
These findings set the stage for further research on the interaction between executive
functions and predictive, habitual processes related to autistic symptoms.
