Ten years ago, Pellicano and Burr published one of the most influential articles in the study
of autism spectrum disorders, linking them to aberrant Bayesian inference processes in the …

According to a recent influential proposal, several phenotypic features of autism spectrum
disorder (ASD) may be accounted for by differences in predictive skills between individuals …

Persistent neuronal spiking has long been considered the mechanism underlying working
memory, but recent proposals argue for alternative 'activity-silent'substrates. Using monkey …

A growing body of research investigates individual differences in the learning of statistical
structure, tying them to variability in cognitive (dis) abilities. This approach views statistical …

Autism is a neurodevelopmental disorder characterized by impaired social skills, motor and
perceptual atypicalities. These difficulties were explained within the Bayesian framework as …

A mechanistic understanding of core cognitive processes, such as working memory, is
crucial to addressing psychiatric symptoms in brain disorders. We propose a combined …

Statistical-learning (SL) theory offers an experience-based account of typical and atypical
spoken and written language acquisition. Recent work has provided initial support for this …

Bayesian theories of autism spectrum disorders (ASD) suggest that atypical predictive
mechanisms could underlie the autistic symptomatology, but little is known about their …

In this article, we develop a computational model of obsessive–compulsive disorder (OCD).
We propose that OCD is characterized by a difficulty in relying on past events to predict the …

Competing theories of dyslexia posit that reading difficulties arise from impaired visual,
auditory, phonological, or statistical learning mechanisms. Importantly, many theories posit …