Abstract
Brain network analysis is one efficient tool in exploring human brain diseases and can differentiate the alterations from comparative networks. The alterations account for time, mental states, tasks, individuals, and so forth. Furthermore, the changes determine the segregation and integration of functional networks that lead to network reorganization (or reconfiguration) to extend the neuroplasticity of the brain. Exploring related brain networks should be of interest that may provide roadmaps for brain research and clinical diagnosis. Recent electroencephalogram (EEG) studies have revealed the secrets of the brain networks and diseases (or disorders) within and between subjects and have provided instructive and promising suggestions and methods. This review summarized the corresponding algorithms that had been used to construct functional or effective networks on the scalp and cerebral cortex. We reviewed EEG network analysis that unveils more cognitive functions and neural disorders of the human and then explored the relationship between brain science and artificial intelligence which may fuel each other to accelerate their advances, and also discussed some innovations and future challenges in the end.
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Adapted from the reference (Li et al. 2018c)
Adapted from the paper (Li et al. 2018a)
Adapted from the material (Privitera 2020)
Adapted from the reference (Li et al. 2018e)
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (#61961160705, #U19A2082, #61901077), the Science and Technology Development Fund, Macau SAR (File no. 0045/2019/AFJ), the Project of Science and Technology Department of Sichuan Province (#2021YFSY0040, #2018JZ0073, #2020ZYD013), and the Key Research and Development Program of Guangdong Province, China (#2018B030339001).
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Luo, C., Li, F., Li, P. et al. A survey of brain network analysis by electroencephalographic signals. Cogn Neurodyn 16, 17–41 (2022). https://doi.org/10.1007/s11571-021-09689-8
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DOI: https://doi.org/10.1007/s11571-021-09689-8