Several competing neuro-computational theories of autism have emerged from predictive coding models of the brain. To disentangle their subtly different predictions about the nature of atypicalities in autistic perception, we performed computational modelling of two sensorimotor tasks: the predictive use of manual gripping forces during object lifting and anticipatory eye movements during a naturalistic interception task. In contrast to some accounts, we found no evidence of chronic atypicalities in the use of priors or weighting of sensory information during object lifting. Differences in prior beliefs, rates of belief updating, and the precision weighting of prediction errors were, however, observed for anticipatory eye movements. Most notably, we observed autism-related difficulties in flexibly adapting learning rates in response to environmental change (i.e., volatility). These findings suggest that atypical encoding of precision and context-sensitive adjustments provide a better explanation of autistic perception than generic attenuation of priors or persistently high precision prediction errors. Our results did not, however, support previous suggestions that autistic people perceive their environment to be persistently volatile.

IDEAS (Interface Design Experience for the Autistic Spectrum) is a method for involving children with Autism Spectrum Disorders (ASD) in the technology design process. This paper extends the IDEAS method to enable use with a design team, providing specific added support for communication and collaboration difficulties that may arise. A study to trial this extended method was conducted with two design teams, each involving three children with ASD, in a series of six, weekly design sessions focused on designing a math game. The findings from this study reveal that the children were able to successfully participate in the sessions and collaborate with other children. The findings also highlight the positive experience that involvement in such a process can offer this population.