Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms

Schizophrenia is a neuropsychiatric disease that affects the nonlinear dynamics of brain activity. The primary objective of this study was to explore the complexity of magnetoencephalograms (MEG) in patients with schizophrenia. We combined a multiscale method and weighted permutation entropy to characterize MEG signals from 19 schizophrenia patients and 16 healthy controls. When the scale was larger than 42, the MEG signals of schizophrenia patients were significantly more complex than those of healthy controls (p < 0.004). The difference in complexity between patients with schizophrenia and the controls was strongest in the frontal and occipital areas (p < 0.001), and there was almost no difference in the central area. In addition, the results showed that the dynamic range of MEG complexity is wider in healthy individuals than in people with schizophrenia. Overall, the multiscale weighted permutation entropy method reliably quantified the complexity of MEG from schizophrenia patients, contributing to the development of potential magnetoencephalographic biomarkers for schizophrenia.

Automated summary

This study aimed to explore the complexity of brain activity in patients with schizophrenia. The results showed that the magnetoencephalographic (MEG) signals of schizophrenia patients were more complex than those of healthy controls, with the strongest difference observed in the frontal and occipital areas. Additionally, healthy individuals had a wider dynamic range of MEG complexity compared to people with schizophrenia.