| Literature DB >> 35126769 |
Cuihua Luo1,2, Fali Li3,4, Peiyang Li5, Chanlin Yi4, Chunbo Li4, Qin Tao4, Xiabing Zhang4, Yajing Si6, Dezhong Yao3,4, Gang Yin7,8, Pengyun Song1,2, Huazhang Wang1,2, Peng Xu3,4.
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.Entities:
Keywords: Artificial intelligence; Brain network analysis; EEG pattern; Neuroplasticity; Segregation and integration
Year: 2021 PMID: 35126769 PMCID: PMC8807775 DOI: 10.1007/s11571-021-09689-8
Source DB: PubMed Journal: Cogn Neurodyn ISSN: 1871-4080 Impact factor: 5.082