Adults with autism overestimate the volatility of the sensory environment

Abstract

Insistence on sameness and intolerance of change are part of the diagnostic criteria for Autism Spectrum Disorder (ASD) but there is little research addressing how people with ASD represent and respond to environmental change. Here, we find that behavioural and pupillometric measurements show adults with ASD are less surprised than neurotypical adults when expectations are violated, with reduced surprise predicting greater symptom severity. A hierarchical Bayesian model of learning suggests that in ASD a tendency to over-learn about volatility in the face of environmental change drives a corresponding reduction in learning about probabilistically aberrant events – putatively rendering them less surprising. Participant-specific modelled estimates of surprise about environmental conditions are linked to pupil size in the ASD group, suggesting heightened phasic noradrenergic responsivity in line with neural gain impairments. This study offers novel insight into the behavioural, algorithmic and physiological mechanisms that underlie responses to environmental volatility in ASD.

From multisensory integration in peripersonal space to bodily self‐consciousness: from statistical regularities to statistical inference

“…Fittingly, multisensory integration is well documented to be anomalous in autism spectrum disorder and schizophrenia (SZ), among other psychopathologies, and these—in particular SZ—are considered to be disorders of the self . Furthermore, much of the recent evidence suggesting deficitary sensory processing in psychopathology is highlighting the presence of either weak or inflexible priors . Anomalously small PPS representations have also been indexed in SZ, suggesting that perhaps these patients do not make use of their stochastic body space.…”

Subjective estimates of uncertainty during gambling and impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

“…A high learning rate suppresses the influence of top-down expectations, and may impair learning about probabilistically aberrant events. In a recent investigation employing the HGF to model surprise about unexpected events, persons with autism learned more quickly about environmental volatility than controls without autism (Lawson et al, 2017). However, at lower levels of the hierarchy, the tendency to believe that environmental instability is unstable resulted in smaller prediction errors (surprise) when events violated expectations.…”

“…However, from the HGF perspective, an agent with increased uncertainty at higher levels would be expected to show both decreased reward and punishment learning, as surprise to both positive and negative unexpected outcomes would be reduced (Lawson et al, 2017). This suggests that LEDD changes may have a secondary role, but further careful experiments will be necessary to address this question.…”

State anxiety biases estimates of uncertainty during reward learning in volatile environments

“…Our study thus provides novel and compelling evidence for abnormal precision estimates underlying impoverished learning in healthy individuals going through temporary states of anxiety. Thus, improper precision weighting could be a general mechanism underlying a range of cognitive biases observed in healthy and psychiatric conditions, such as "hysteria" or autism (Edwards et al, 2012;Lawson et al, 2017).…”

“…Examinations of belief, uncertainty, and precision estimates using Bayesian formulations in perceptual and learning tasks are increasingly used to provide mechanistic explanations for an array of neuropsychiatric conditions. Specifically, difficulties estimating precision have been suggested to explain various clinical expressions, from movement difficulties in Parkinson's disease to features of schizophrenia and autism (Friston et al, 2016Lawson et al, 2017Lawson et al, , 2014Parr et al, 2018). In the case of anxiety, altered beliefs are also theorised to play a vital role (Paulus and Stein, 2010;Paulus and Yu, 2012).…”