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Altered Brain Criticality in Schizophrenia: New Insights From Magnetoencephalography.
Alamian, Golnoush; Lajnef, Tarek; Pascarella, Annalisa; Lina, Jean-Marc; Knight, Laura; Walters, James; Singh, Krish D; Jerbi, Karim.
Afiliación
  • Alamian G; CoCo Lab, Department of Psychology, Université de Montréal, Montréal, QC, Canada.
  • Lajnef T; CoCo Lab, Department of Psychology, Université de Montréal, Montréal, QC, Canada.
  • Pascarella A; Institute for Applied Mathematics Mauro Picone, National Research Council, Roma, Italy.
  • Lina JM; Department of Electrical Engineering, École de Technologie Supérieure, Montréal, QC, Canada.
  • Knight L; Mathematical Research Center, Université de Montréal, Montréal, QC, Canada.
  • Walters J; Centre UNIQUE, Union Neurosciences et Intelligence Artificielle - Québec, Montréal, QC, Canada.
  • Singh KD; CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom.
  • Jerbi K; Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, United Kingdom.
Front Neural Circuits ; 16: 630621, 2022.
Article en En | MEDLINE | ID: mdl-35418839
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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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Esquizofrenia / Magnetoencefalografía Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Esquizofrenia / Magnetoencefalografía Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article