ArticlePloS one2023
Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis.Psychiatry and clinical neurosciences · 2024Pooled it
- Dynamic Functional Synchronization Profiles in Autism Differ by Spatial Scale and Along Hierarchical Cortical Gradients.Biological psychiatry global open science · 2026Article
- A three-component dynamical index of consciousness-related neural organisation.Biological cybernetics · 2026Article
- Brain dynamics of attentional, default-mode and limbic networks are disrupted at rest in post-COVID-19 syndrome.Brain, behavior, & immunity - health · 2026Article
- Riemannian geometry meets fMRI: the advantages of modeling correlation manifolds and eigenvector subspaces.Research square · 2026Article
- Energy-Based Phase-Locking State Analysis in Brain State Identification.Human brain mapping · 2026Article
- Neuromodulation-induced normalization of cortical metastable dynamics signatures in Parkinson's disease.NPJ Parkinson's disease · 2026Article
- From microstates to macroscales: A Critical Review of Maximum Entropy Modeling and Energy Landscape Analysis in functional MRI.Research square · 2025Article
- NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders.Proceedings of machine learning research · 2025Article
- Development of brain metastable dynamics during the equivalent of the third gestational trimester.Developmental cognitive neuroscience · 2025Review
- DySCo: A general framework for dynamic functional connectivity.PLoS computational biology · 2025Article
- Metastability demystified - the foundational past, the pragmatic present and the promising future.Nature reviews. Neuroscience · 2025Review
- Exploring psychedelic-assisted therapy in the treatment of functional seizures: A review of underlying mechanisms and associated brain networks.Journal of psychopharmacology (Oxford, England) · 2024Review
- EiDA: A lossless approach for dynamic functional connectivity; application to fMRI data of a model of ageing.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Emergence of metastability in frustrated oscillatory networks: the key role of hierarchical modularity.Frontiers in network physiology · 2024Article
- Exploring global and local processes underlying alterations in resting-state functional connectivity and dynamics in schizophrenia.Frontiers in psychiatry · 2024Article
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Authors and funding
6 authors.
Funding
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.
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