AUTHOR=Zhu Yan , Zhu Geng , Li Bin , Yang Yueqi , Zheng Xiaohan , Xu Qi , Li Xiaoou 

TITLE=Abnormality of Functional Connections in the Resting State Brains of Schizophrenics

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 16 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2022.799881

DOI=10.3389/fnhum.2022.799881

ISSN=1662-5161

ABSTRACT=To explore the change of brain connectivity in schizophrenics (SCZ), resting state EEG source functional connections of SCZ and healthy control (HC) were investigated in the paper. Different band single-layer networks, multi-layer network, and improved multi-layer network were constructed and their topological attributes were extracted. The topological attributes of SCZ and HC were automatically distinguished using machine learning methods and the effectiveness of different network construction methods were compared based on the classification accuracy. The results showed that the classification accuracy was 89.38% for α band network, 83.75% for multi-layer network, and 84.38% for improved multi-layer network. Compared SCZ with Alzheimer disease (AD) patients, the classification accuracy of improved multi-layer network was the highest, which was 82.5%. The power spectrum in α band of SCZ was significantly lower than HC, while there was no significant difference between SCZ and AD. This indicated that the improved multi-layer network can effectively distinguish SCZ and other groups not only when their power spectrum was significantly different. The results also suggested that the improved multi-layer topological attributes were regarded as biological markers in the clinical diagnosis of patients with schizophrenia and even other mental disorders.