Post published on Twitter/X on 19 Sep 2021 12:44

Abstract

Predictive coding theories of autism suggest that symptoms could result from an atypical learning of expectations. We assessed whether adults with autism could learn expectations in an uncertain context. Twenty-nine neurotypicals and 25 autistic adults participated in an associative learning task. After hearing a tone, participants had to predict the rotation direction of a dot pair, and to report what they perceived. There was a probabilistic association between the tone and the rotation direction. This association could reverse within a block. Both groups were biased by their expectations, as they reported perceiving a rotation consistent with the contingency in a subset of ambiguous trials where the dots did not rotate. Participants made predictions above chance level, but contrary to neurotypicals, autistic participants updated their prior expectation less after a change in contingency. Computational modeling revealed a smaller influence of associative learning on perceptual expectations in the autism group. In an additional task, participants reported how confident they were about their percepts. Both groups expressed confidence in relation to the stimuli, but certainty ratings reflected response times in neurotypical participants only. These findings, showing a more inflexible adjustment of priors in autism, should help refining the predictive coding hypotheses of autism. Lay abstract We have an internal representation of the world that guides our behavior, helps us predicting what comes next and therefore, reducing uncertainty. For instance, after hearing the noise of a door opening, we usually expect to see a person appearing, whose features differ depending on the context. In this example of associative learning, predictions need to be adjusted if there is a change in the environment (e.g. different person depending on the location). Recent theories suggest that the symptoms encountered in autism could be due to an atypical learning of predictions or to a decreased influence of these expectations on perception. Here, we conducted an experiment assessing whether adults with autism could learn and adjust their predictions in a changing environment. Throughout a behavioral task, participants learned to associate a sound with a visual outcome, but this association could sometimes reverse. Results showed that autistic adults could learn to make predictions that fitted the main sound–vision association, but were slower to adapt their expectations when there was an unannounced change in the environment. We also observed that both adults with and without autism tended to be biased by their expectations, as they reported seeing what they expected to see rather than what was actually shown. Altogether, our results indicate that autistic adults can learn predictions but are more inflexible to adjust these predictions in a changing environment. These results help refining recent theories of autism (called “predictive coding” theories), which intend to identify the core mechanisms underlying the autistic symptomatology.