Visual perceptual inference and the affective consequences of perceptual uncertainty in children with Autism Spectrum Disorder

Children with Autism Spectrum Disorder (ASD) show a broad spectrum of symptoms, ranging from social communication and interaction difficulties to restricted and repetitive behaviours, often with co-occurring perceptual difficulties and anxiety. Explaining these heterogeneous symptoms is challenging. Recently, unifying mechanistic theories based on predictive coding have been developed. Predictive coding describes typical cognition by processes of making and testing predictions regarding the outside world.
One promising explanatory account argues that the errors resulting from violations to predictions are continuously given high and inflexible weights in ASD (High and Inflexible Precision of Prediction Errors; HIPPEA). These unconscious chronic prediction difficulties might also explain the often reported and highly impacting anxiety symptoms in ASD.
In this project, we will try to unravel the computational and neural mechanisms of predictive coding in children with ASD by employing strong experimental paradigms with established computational models from the field of visual perception, combined with fMRI. In addition, we will test the hypotheses regarding stress and anxiety with physiological stress measures and a set of questionnaires. Besides the high theoretical impact, gaining insight into the neurobiological underpinnings of ASD and the underlying mechanisms of stress and anxiety might improve clinical care for children with ASD.