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Predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model.
Tarasi, Luca; Trajkovic, Jelena; Diciotti, Stefano; di Pellegrino, Giuseppe; Ferri, Francesca; Ursino, Mauro; Romei, Vincenzo.
Afiliação
  • Tarasi L; Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum - Università di Bologna, Campus di Cesena, 47521 Cesena, Italy. Electronic address: luca.tarasi2@unibo.it.
  • Trajkovic J; Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum - Università di Bologna, Campus di Cesena, 47521 Cesena, Italy.
  • Diciotti S; Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Cesena, Italy; Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy.
  • di Pellegrino G; Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum - Università di Bologna, Campus di Cesena, 47521 Cesena, Italy.
  • Ferri F; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
  • Ursino M; Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", University of Bologna, Cesena, Italy.
  • Romei V; Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum - Università di Bologna, Campus di Cesena, 47521 Cesena, Italy; IRCCS Fondazione Santa Lucia, 00179 Rome, Italy. Electronic address: vincenzo.romei@unibo.it.
Neurosci Biobehav Rev ; 132: 1-22, 2022 01.
Article em En | MEDLINE | ID: mdl-34774901
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia / Transtorno Autístico / Transtorno do Espectro Autista Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Neurosci Biobehav Rev Ano de publicação: 2022 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia / Transtorno Autístico / Transtorno do Espectro Autista Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Neurosci Biobehav Rev Ano de publicação: 2022 Tipo de documento: Article País de publicação: Estados Unidos