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Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology
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 functiona...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035891/ https://www.ncbi.nlm.nih.gov/pubmed/36952467 http://dx.doi.org/10.1371/journal.pone.0282707 |
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author | Hancock, Fran Rosas, Fernando E. McCutcheon, Robert A. Cabral, Joana Dipasquale, Ottavia Turkheimer, Federico E. |
author_facet | Hancock, Fran Rosas, Fernando E. McCutcheon, Robert A. Cabral, Joana Dipasquale, Ottavia Turkheimer, Federico E. |
author_sort | Hancock, Fran |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10035891 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100358912023-03-24 Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology Hancock, Fran Rosas, Fernando E. McCutcheon, Robert A. Cabral, Joana Dipasquale, Ottavia Turkheimer, Federico E. PLoS One Research Article 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. Public Library of Science 2023-03-23 /pmc/articles/PMC10035891/ /pubmed/36952467 http://dx.doi.org/10.1371/journal.pone.0282707 Text en © 2023 Hancock et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hancock, Fran Rosas, Fernando E. McCutcheon, Robert A. Cabral, Joana Dipasquale, Ottavia Turkheimer, Federico E. Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
title | Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
title_full | Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
title_fullStr | Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
title_full_unstemmed | Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
title_short | Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
title_sort | metastability as a candidate neuromechanistic biomarker of schizophrenia pathology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035891/ https://www.ncbi.nlm.nih.gov/pubmed/36952467 http://dx.doi.org/10.1371/journal.pone.0282707 |
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