Gray matter matters: Cognitive stability and flexibility in schizophrenia spectrum disorder.

cognitive stability and flexibility frontostriatal networks gray matter volume prediction errors schizophrenia

Journal

Psychophysiology
ISSN: 1469-8986
Titre abrégé: Psychophysiology
Pays: United States
ID NLM: 0142657

Informations de publication

Date de publication:
01 May 2024
Historique:
revised: 12 03 2024
received: 20 12 2023
accepted: 10 04 2024
medline: 1 5 2024
pubmed: 1 5 2024
entrez: 1 5 2024
Statut: aheadofprint

Résumé

Cognitive dysfunction constitutes a core characteristic of schizophrenia spectrum disorders (SZ). Specifically, deficits in updating generative models (i.e., cognitive flexibility) and shielding against distractions (i.e., cognitive stability) are considered critical contributors to cognitive impairment in these patients. Here, we examined the structural integrity of frontostriatal networks and their associations with reduced cognitive stability and flexibility in SZ patients. In a sample of 21 patients diagnosed with SZ and 22 healthy controls, we measured gray matter volume (GMV) using structural MRI. Further, cognitive stability and flexibility were assessed using a switch-drift paradigm, quantifying the successful ignoring of distracters and detection of rule switches. Compared to controls, patients showed significantly smaller GMV in the whole brain and three predefined regions of interest: the medial prefrontal cortex (mPFC), inferior frontal gyrus (IFG), and caudate nucleus (CN). Notably, GMV in these areas positively correlated with correct rule-switch detection but not with ignoring rule-compatible drifts. Further, the volumetric differences between SZ patients and controls were statistically explainable by considering the behavioral performance in the switch-drift task. Our results indicate that morphological abnormalities in frontostriatal networks are associated with deficient flexibility in SZ patients and highlight the necessity of minimizing neurodevelopmental and progressive brain atrophy in this population.

Identifiants

pubmed: 38691383
doi: 10.1111/psyp.14596
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e14596

Subventions

Organisme : Medical Faculty of the University of Muenster
Organisme : Deutsche Forschungsgemeinschaft
ID : FOR2107 DA1151/5-1
Organisme : Deutsche Forschungsgemeinschaft
ID : DA1151/5-2
Organisme : Deutsche Forschungsgemeinschaft
ID : SFB-TRR58
Organisme : Deutsche Forschungsgemeinschaft
ID : C09
Organisme : Deutsche Forschungsgemeinschaft
ID : Z02
Organisme : the Interdisciplinary Center for Clinical Research (IZKF) of the Medical Faculty of the University of Muenster
ID : Dan3/012/17

Informations de copyright

© 2024 The Authors. Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research.

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Auteurs

Florentine Herkströter (F)

Department of Neurology, Niels-Stensen-Kliniken, Marienhospital Osnabrück-Standort Natruper Holz, Osnabrueck, Germany.

Anoushiravan Zahedi (A)

Institute of Psychology, University of Muenster, Muenster, Germany.
Otto Creutzfeldt-Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany.

Isabel Standke (I)

Institute for Translational Psychiatry, University of Muenster, Muenster, Germany.

Udo Dannlowski (U)

Institute of Psychology, University of Muenster, Muenster, Germany.
Institute for Translational Psychiatry, University of Muenster, Muenster, Germany.

Rebekka Lencer (R)

Institute for Translational Psychiatry, University of Muenster, Muenster, Germany.
Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany.

Ricarda I Schubotz (RI)

Institute of Psychology, University of Muenster, Muenster, Germany.
Otto Creutzfeldt-Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany.

Ima Trempler (I)

Institute of Psychology, University of Muenster, Muenster, Germany.
Otto Creutzfeldt-Center for Cognitive and Behavioral Neuroscience, University of Muenster, Muenster, Germany.

Classifications MeSH