Altered brain criticality in Schizophrenia: New insights from MEG

Abstract

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.

New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment

“…Alpha and beta band activity was correlated with disrupted temporal connectivity in (para) limbic areas 10.3389/fncel. 2024.1386583 Frontiers in Cellular Neuroscience 04 frontiersin.org and associated with reduced signal memory and higher variability across time in SZ patients (Alamian et al, 2020). Several neuronalbased alterations seem to contribute to CIAS, including abnormalities in neurotransmitter systems, structural/functional changes (Karlsgodt et al, 2010;Zhao et al, 2018;Sone et al, 2022), impaired synaptic plasticity, and deviations in neural oscillations.…”

Outlier detection and removal in multifractal analysis of electrophysiological brain signals

“…While the neuroscience community working on the brain criticality hypothesis has paid attention to the low-frequency fluctuations of neuronal oscillations [2], the multifractal literature in neuroscience has focused on characterizing the low-frequency fluctuations of the broadband recordings of brain activity [10][11][12][13][14]. Overall, MFA as a tool in neuroscience has seen relatively few developments.…”