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Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.
Hancock, Fran; Rosas, Fernando E; McCutcheon, Robert A; Cabral, Joana; Dipasquale, Ottavia; Turkheimer, Federico E.
Afiliação
  • Hancock F; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, United Kingdom.
  • Rosas FE; Department of Informatics, University of Sussex, Brighton, United Kingdom.
  • McCutcheon RA; Centre for Psychedelic Research, Department of Brain Science, Imperial College London, London, United Kingdom.
  • Cabral J; Centre for Complexity Science, Imperial College London, London, United Kingdom.
  • Dipasquale O; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom.
  • Turkheimer FE; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, United Kingdom.
PLoS One ; 18(3): e0282707, 2023.
Article em En | MEDLINE | ID: mdl-36952467
ABSTRACT
The disconnection hypothesis of schizophrenia proposes that symptoms of the disorder arise as a result of aberrant functional integration between segregated areas of the brain. The concept of metastability characterizes the coexistence of competing tendencies for functional integration and functional segregation in the brain, and is therefore well suited for the study of schizophrenia. In this study, we investigate metastability as a candidate neuromechanistic biomarker of schizophrenia pathology, including a demonstration of reliability and face validity. Group-level discrimination, individual-level classification, pathophysiological relevance, and explanatory power were assessed using two independent case-control studies of schizophrenia, the Human Connectome Project Early Psychosis (HCPEP) study (controls n = 53, non-affective psychosis n = 82) and the Cobre study (controls n = 71, cases n = 59). In this work we extend Leading Eigenvector Dynamic Analysis (LEiDA) to capture specific features of dynamic functional connectivity and then implement a novel approach to estimate metastability. We used non-parametric testing to evaluate group-level differences and a naïve Bayes classifier to discriminate cases from controls. Our results show that our new approach is capable of discriminating cases from controls with elevated effect sizes relative to published literature, reflected in an up to 76% area under the curve (AUC) in out-of-sample classification analyses. Additionally, our new metric showed explanatory power of between 81-92% for measures of integration and segregation. Furthermore, our analyses demonstrated that patients with early psychosis exhibit intermittent disconnectivity of subcortical regions with frontal cortex and cerebellar regions, introducing new insights about the mechanistic bases of these conditions. Overall, these findings demonstrate reliability and face validity of metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Esquizofrenia / Conectoma Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Esquizofrenia / Conectoma Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido