ArticleFrontiers in neural circuits2022
Altered Brain Criticality in Schizophrenia: New Insights From Magnetoencephalography.
Article in Frontiers in neural circuits, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Cortical Structures Underlying Schizophrenia and Sex Differences in Preadolescents: An Adolescent Brain Cognitive Development Study.Child psychiatry and human development · 2026Article
- Critical Dynamics in the Association Cortex Predict Higher Intelligence in Typically Developing Children.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Static and Dynamic Cross-Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients.Human brain mapping · 2025Article
- Static and Dynamic Cross-Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients.bioRxiv : the preprint server for biology · 2024Article
- A synergetic turn in cognitive neuroscience of brain diseases.Trends in cognitive sciences · 2024Review
- Structural Modularity Tunes Mesoscale Criticality in Biological Neuronal Networks.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Opposite effects of positive and negative symptoms on resting-state brain networks in schizophrenia.Communications biology · 2023Article
- Fractal Structure of Brain Electrical Activity of Patients With Mental Disorders.Frontiers in physiology · 2022Article
- Quasicriticality explains variability of human neural dynamics across life span.Frontiers in computational neuroscience · 2022Article
- Clusters of psychosis: compensation as a contributor to the heterogeneity of schizophrenia.Journal of psychiatry & neuroscience : JPNArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Schizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements toward a central biomarker are still lacking. One of the missing pieces is a better understanding of how non-linear neural dynamics are altered in this patient population. In this study, the resting-state neuromagnetic signals of schizophrenia patients and healthy controls were analyzed in the framework of criticality. When biological systems like the brain are in a state of criticality, they are thought to be functioning at maximum efficiency (e.g., optimal communication and storage of information) and with maximum adaptability to incoming information. Here, we assessed the self-similarity and multifractality of resting-state brain signals recorded with magnetoencephalography in patients with schizophrenia patients and in matched controls. Schizophrenia patients had similar, although attenuated, patterns of self-similarity and multifractality values. Statistical tests showed that patients had higher values of self-similarity than controls in fronto-temporal regions, indicative of more regularity and memory in the signal. In contrast, patients had less multifractality than controls in the parietal and occipital regions, indicative of less diverse singularities and reduced variability in the signal. In addition, supervised machine-learning, based on logistic regression, successfully discriminated the two groups using measures of self-similarity and multifractality as features. Our results provide new insights into the baseline cognitive functioning of schizophrenia patients by identifying key alterations of criticality properties in their resting-state brain data.
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