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.

Tarasi L., Trajkovic J., Diciotti S., Di Pellegrino G., Ferri F., Ursino M., et al. (2022). Predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 132(January 2022), 1-22 [10.1016/j.neubiorev.2021.11.006].

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

Tarasi L.
;
Diciotti S.;Di Pellegrino G.;Ursino M.;Romei V.
2022

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.
2022
Tarasi L., Trajkovic J., Diciotti S., Di Pellegrino G., Ferri F., Ursino M., et al. (2022). Predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 132(January 2022), 1-22 [10.1016/j.neubiorev.2021.11.006].
Tarasi L.; Trajkovic J.; Diciotti S.; Di Pellegrino G.; Ferri F.; Ursino M.; Romei V.
File in questo prodotto:
File Dimensione Formato  
predictive+waves+post+print.pdf

Open Access dal 25/05/2023

Tipo: Postprint
Licenza: Creative commons
Dimensione 581.23 kB
Formato Adobe PDF
581.23 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/842867
Citazioni
  • ???jsp.display-item.citation.pmc??? 16
  • Scopus 31
  • ???jsp.display-item.citation.isi??? 30
social impact