Low-level, prediction-based sensory and motor processes are unimpaired in Autism

Johanna J.S Finnemann,Kate Plaisted-Grant,James Moore,Christoph Teufel,Paul C Fletcher

doi:10.1016/j.neuropsychologia.2021.107835

Johanna J.S Finnemann, Kate Plaisted-Grant + Show 3 more

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https://doi.org/10.1016/j.neuropsychologia.2021.107835

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Abstract

A new promising account of human brain function suggests that sensory cortices try to optimise information processing via predictions that are based on prior experiences. The brain is thus likened to a probabilistic prediction machine. There has been a growing - though inconsistent - literature to suggest that features of autism spectrum conditions (ASCs) are associated with a deficit in modelling the world through such prediction-based inference. However empirical evidence for differences in low-level sensorimotor predictions in autism is still lacking. One approach to examining predictive processing in the sensorimotor domain is in the context of self-generated (predictable) as opposed to externally-generated (less predictable) effects. We employed two complementary tasks - forcematching and intentional binding - which examine self-versus externally-generated action effects in terms of sensory attenuation and intentional binding respectively in adults with and without autism. The results show that autism was associated with normal levels of sensory attenuation of internally-generated force and with unaltered temporal attraction of voluntary actions and their outcomes. Thus, our results do not support a general deficit in predictive processing in autism.

Highlights

The predictive processing framework accounts for how we deal optimally with ambiguous signals from our environment using prediction-based optimisation of inference (Teufel and Fletcher [1], Friston and Kiebel [2])
We found no evidence of a deficit in the attenuation of selfproduced sensory consequences in autism, which is in contradiction of existing predictive processing models of the condition
A Bayesian analysis supported an absence of group differences in key measures of sensory attenuation

Summary

Introduction

The predictive processing framework accounts for how we deal optimally with ambiguous signals from our environment using prediction-based optimisation of inference (Teufel and Fletcher [1], Friston and Kiebel [2]). Burr [15] suggesting that predictive deficits in individuals with autism are due to a diminished effect of prior expectations on the processing of ambiguous sensory information, leading to inferences that are more strongly based on sensory information. This atypicality in information processing, they speculate, could be a consequence of excessive endogenous neural noise others have pointed out that reduced endogenous noise could yield comparable outcomes (Brock [21]). Alternative accounts suggest that the problem lies not in the prior expectations themselves but in altered precision of the prediction error - a key feedforward signal in the processing hierarchy (Van de Cruys et al [22], Lawson et al [17])

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