Adjustment of Synchronization Stability of Dynamic Brain-Networks Based on Feature Fusion - Li, Haifang; Yao, Rong; Xia, Xiaoluan; Yin, Guimei; Deng, Hongxia; Yang, Pengfei (Frontiers in Human Neuroscience, 2019)
One aspect of difficult-to-cure neurological diseases is a lack of or an anomaly of the brain's overall or local integration processing. When these work together, the process is referred to as the synchronization phenomenon in neurobiological theory. By studying the synchronization capabilities of the brain-network, we can intensively describe and characterize both the state of the interactions between brain regions and their differences between people with a mental illness and a set of controls by measuring the rapid changes in brain activity in patients with psychiatric disorders and the strength and integrity of their entire brain network. This is significant for the study of mental illness. In view of the shortcomings of the static connection method, this paper introduces the concepts of "dynamic" and "time-varying", constructs an EEG brain function network based on dynamic connection, and analyzes the time-varying characteristics of the EEG functional network. We used the spectral features of the brain network to extract its synchronization features and used the synchronization features to describe the evolutionary process and differences in the brain network’s synchronization ability between a group of patients and a control group during a working memory task. We propose a method based on the fusion of traditional features and spectral features to achieve an adjustment of the patient's brain network synchronization ability, so that its synchronization ability can be made to be consistent with that of healthy subjects, theoretically achieving the purpose of the treatment of diseases. Studying the stability of brain network synchronization can provide new ideas about the pathogenic mechanism and cure of mental diseases and has a wide range of application possibilities.