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Predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model

Highlights

ASD and SSD lie on two poles of the same predictive continuum.

ASD is characterized by a bias towards prediction-error’s overweighting.

SSD tends to overestimate the precision of their predictive models.

Brain oscillations are crucial in the transmission of prediction and prediction error.

Different oscillatory profiles account for the predictive styles of ASD and SSD.

Abstract

The
brain is a predictive machine. Converging data suggests a diametric
predictive strategy from autism spectrum disorders (ASD) to
schizophrenic spectrum disorders (SSD). Whereas perceptual inference in
ASD is rigidly shaped by incoming sensory information, the SSD
population is prone to overestimate the precision of their priors’
models. Growing evidence considers brain oscillations pivotal biomarkers
to understand how top-down predictions integrate bottom-up input.
Starting from the conceptualization of ASD and SSD as oscillopathies, we
introduce an integrated perspective that ascribes the maladjustments of
the predictive mechanism to dysregulation of neural synchronization.
According to this proposal, disturbances in the oscillatory profile do
not allow the appropriate trade-off between descending predictive
signal, overweighted in SSD, and ascending prediction errors,
overweighted in ASD. These opposing imbalances both result in an
ill-adapted reaction to external challenges. This approach offers a
neuro-computational model capable of linking predictive coding theories
with electrophysiological findings, aiming to increase knowledge on the
neuronal foundations of the two spectra features and stimulate
hypothesis-driven rehabilitation/research perspectives.

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