Literature DB >> 29860087

Decision-making in schizophrenia: A predictive-coding perspective.

Philipp Sterzer1, Martin Voss2, Florian Schlagenhauf2, Andreas Heinz3.   

Abstract

Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences.
Copyright © 2018 Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29860087     DOI: 10.1016/j.neuroimage.2018.05.074

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  16 in total

Review 1.  A review of risky decision-making in psychosis-spectrum disorders.

Authors:  John R Purcell; Emma N Herms; Jaime Morales; William P Hetrick; Krista M Wisner; Joshua W Brown
Journal:  Clin Psychol Rev       Date:  2021-12-20

2.  Elevation of EGR1/zif268, a Neural Activity Marker, in the Auditory Cortex of Patients with Schizophrenia and its Animal Model.

Authors:  Yuriko Iwakura; Ryoka Kawahara-Miki; Satoshi Kida; Hidekazu Sotoyama; Ramil Gabdulkhaev; Hitoshi Takahashi; Yasuto Kunii; Mizuki Hino; Atsuko Nagaoka; Ryuta Izumi; Risa Shishido; Toshiyuki Someya; Hirooki Yabe; Akiyoshi Kakita; Hiroyuki Nawa
Journal:  Neurochem Res       Date:  2022-04-25       Impact factor: 4.414

Review 3.  Illusions, Delusions, and Your Backwards Bayesian Brain: A Biased Visual Perspective.

Authors:  Richard T Born; Gianluca M Bencomo
Journal:  Brain Behav Evol       Date:  2021-03-30       Impact factor: 1.808

4.  Aberrant Cortical Connectivity During Ambiguous Object Recognition Is Associated With Schizophrenia.

Authors:  Victor J Pokorny; Tori D Espensen-Sturges; Philip C Burton; Scott R Sponheim; Cheryl A Olman
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2020-10-10

Review 5.  Rethinking delusions: A selective review of delusion research through a computational lens.

Authors:  Brandon K Ashinoff; Nicholas M Singletary; Seth C Baker; Guillermo Horga
Journal:  Schizophr Res       Date:  2021-03-03       Impact factor: 4.662

6.  Unification by Fiat: Arrested Development of Predictive Processing.

Authors:  Piotr Litwin; Marcin Miłkowski
Journal:  Cogn Sci       Date:  2020-07

7.  Disturbed time experience during and after psychosis.

Authors:  D H V Vogel; T Beeker; T Haidl; C Kupke; M Heinze; K Vogeley
Journal:  Schizophr Res Cogn       Date:  2019-03-21

Review 8.  Cerebellum, Predictions and Errors.

Authors:  Laurentiu S Popa; Timothy J Ebner
Journal:  Front Cell Neurosci       Date:  2019-01-15       Impact factor: 5.505

9.  Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry.

Authors:  Jessica P Y Hua; Nicole R Karcher; Kelsey T Straub; John G Kerns
Journal:  Brain Imaging Behav       Date:  2021-07-04       Impact factor: 3.978

10.  Corpus callosum morphology in major mental disorders: a magnetic resonance imaging study.

Authors:  Fabrizio Piras; Daniela Vecchio; Florian Kurth; Federica Piras; Nerisa Banaj; Valentina Ciullo; Eileen Luders; Gianfranco Spalletta
Journal:  Brain Commun       Date:  2021-05-11
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