Aberrant connectivity in auditory precision encoding in schizophrenia spectrum disorder and across the continuum of psychotic-like experiences.

Dynamic causal modelling EEG MMN Posterior probability maps Psychosis Schizophrenia Schizotypy

Journal

Schizophrenia research
ISSN: 1573-2509
Titre abrégé: Schizophr Res
Pays: Netherlands
ID NLM: 8804207

Informations de publication

Date de publication:
08 2020
Historique:
received: 19 02 2020
revised: 11 05 2020
accepted: 27 05 2020
pubmed: 1 7 2020
medline: 19 5 2021
entrez: 29 6 2020
Statut: ppublish

Résumé

The ability to generate a precise internal model of statistical regularities is impaired in schizophrenia. Predictive coding accounts of schizophrenia suggest that psychotic symptoms may be explained by a failure to build precise beliefs or a model of the world. The precision of this model may vary with context. For example, in a noisy environment the model will be more imprecise compared to a model built in an environment with lower noise. However compelling, this idea has not yet been empirically studied in schizophrenia. In this study, 62 participants engaged in a stochastic mismatch negativity paradigm with high and low precision. We included inpatients with a schizophrenia spectrum disorder (N = 20), inpatients with a psychiatric disorder but without psychosis (N = 20), and healthy controls (N = 22), with comparable sex ratio and age distribution. Bayesian mapping and dynamic causal modelling were employed to investigate the underlying microcircuitry of precision encoding of auditory stimuli. We found strong evidence (exceedance P > 0.99) for differences in the underlying connectivity associated with precision encoding between the three groups as well as on the continuum of psychotic-like experiences assessed across all participants. Critically, we show changes in interhemispheric connectivity between the two inpatient groups, with some connections further aligning on the continuum of psychotic-like experiences. While our results suggest continuity in backward connectivity alterations with psychotic-like experiences regardless of diagnosis, they also point to specificity for the schizophrenia spectrum disorder group in interhemispheric connectivity alterations.

Sections du résumé

BACKGROUND
The ability to generate a precise internal model of statistical regularities is impaired in schizophrenia. Predictive coding accounts of schizophrenia suggest that psychotic symptoms may be explained by a failure to build precise beliefs or a model of the world. The precision of this model may vary with context. For example, in a noisy environment the model will be more imprecise compared to a model built in an environment with lower noise. However compelling, this idea has not yet been empirically studied in schizophrenia.
METHODS
In this study, 62 participants engaged in a stochastic mismatch negativity paradigm with high and low precision. We included inpatients with a schizophrenia spectrum disorder (N = 20), inpatients with a psychiatric disorder but without psychosis (N = 20), and healthy controls (N = 22), with comparable sex ratio and age distribution. Bayesian mapping and dynamic causal modelling were employed to investigate the underlying microcircuitry of precision encoding of auditory stimuli.
RESULTS
We found strong evidence (exceedance P > 0.99) for differences in the underlying connectivity associated with precision encoding between the three groups as well as on the continuum of psychotic-like experiences assessed across all participants. Critically, we show changes in interhemispheric connectivity between the two inpatient groups, with some connections further aligning on the continuum of psychotic-like experiences.
CONCLUSIONS
While our results suggest continuity in backward connectivity alterations with psychotic-like experiences regardless of diagnosis, they also point to specificity for the schizophrenia spectrum disorder group in interhemispheric connectivity alterations.

Identifiants

pubmed: 32593736
pii: S0920-9964(20)30341-8
doi: 10.1016/j.schres.2020.05.061
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

185-194

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

Kit Melissa Larsen (KM)

Queensland Brain Institute, The University of Queensland, Australia; Australian Research Council of Excellence for Integrative Brain Function, Australia; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Child and Adolescent Mental Health Centre, Mental Health Services Capital Region Copenhagen, University of Copenhagen, Denmark. Electronic address: melissal@drcmr.dk.

Ilvana Dzafic (I)

Queensland Brain Institute, The University of Queensland, Australia; Australian Research Council of Excellence for Integrative Brain Function, Australia; Melbourne School of Psychological Sciences, University of Melbourne, Australia.

Hayley Darke (H)

Melbourne School of Psychological Sciences, University of Melbourne, Australia.

Holly Pertile (H)

Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC, Australia; Monash Medical Centre, Monash Health, Clayton, VIC, Australia.

Olivia Carter (O)

Melbourne School of Psychological Sciences, University of Melbourne, Australia.

Suresh Sundram (S)

Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC, Australia; Monash Medical Centre, Monash Health, Clayton, VIC, Australia.

Marta I Garrido (MI)

Queensland Brain Institute, The University of Queensland, Australia; Australian Research Council of Excellence for Integrative Brain Function, Australia; Melbourne School of Psychological Sciences, University of Melbourne, Australia; Centre for Advanced Imaging, The University of Queensland, Australia.

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