RT Journal Article SR Electronic T1 Altered brain criticality in Schizophrenia: New insights from MEG JF bioRxiv FD Cold Spring Harbor Laboratory SP 2021.11.09.467906 DO 10.1101/2021.11.09.467906 A1 Golnoush Alamian A1 Tarek Lajnef A1 Annalisa Pascarella A1 Jean-Marc Lina A1 Laura Knight A1 James Walters A1 Krish D Singh A1 Karim Jerbi YR 2021 UL http://biorxiv.org/content/early/2021/11/13/2021.11.09.467906.abstract AB Schizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements towards 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. Our analysis showed a clear ascending, rostral to caudal gradient of self-similarity values in healthy controls, and an opposite gradient for multifractality (descending values, rostral to caudal). Schizophrenia patients had similar, although attenuated, gradients 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.Competing Interest StatementThe authors have declared no competing interest.