Literature DB >> 35126769

A survey of brain network analysis by electroencephalographic signals.

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.
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.

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


  244 in total

1.  Detecting large-scale networks in the human brain using high-density electroencephalography.

Authors:  Quanying Liu; Seyedehrezvan Farahibozorg; Camillo Porcaro; Nicole Wenderoth; Dante Mantini
Journal:  Hum Brain Mapp       Date:  2017-06-20       Impact factor: 5.038

2.  Dynamical causal modelling for M/EEG: spatial and temporal symmetry constraints.

Authors:  Matthias Fastenrath; Karl J Friston; Stefan J Kiebel
Journal:  Neuroimage       Date:  2008-07-30       Impact factor: 6.556

3.  On the neural mechanisms subserving consciousness and attention.

Authors:  Catherine Tallon-Baudry
Journal:  Front Psychol       Date:  2012-01-09

4.  EEG-based functional brain networks: does the network size matter?

Authors:  Amir Joudaki; Niloufar Salehi; Mahdi Jalili; Maria G Knyazeva
Journal:  PLoS One       Date:  2012-04-25       Impact factor: 3.240

5.  The enhanced information flow from visual cortex to frontal area facilitates SSVEP response: evidence from model-driven and data-driven causality analysis.

Authors:  Fali Li; Yin Tian; Yangsong Zhang; Kan Qiu; Chunyang Tian; Wei Jing; Tiejun Liu; Yang Xia; Daqing Guo; Dezhong Yao; Peng Xu
Journal:  Sci Rep       Date:  2015-10-05       Impact factor: 4.379

6.  The reliability of estimating visual working memory capacity.

Authors:  Mengnuo Dai; Yanju Li; Shuoqiu Gan; Feng Du
Journal:  Sci Rep       Date:  2019-02-04       Impact factor: 4.379

7.  Use of Multiple EEG Features and Artificial Neural Network to Monitor the Depth of Anesthesia.

Authors:  Yue Gu; Zhenhu Liang; Satoshi Hagihira
Journal:  Sensors (Basel)       Date:  2019-05-31       Impact factor: 3.576

8.  Computer-Aided Tinnitus Detection based on Brain Network Analysis of EEG Functional Connectivity.

Authors:  F Mohagheghian; B Makkiabadi; H Jalilvand; H Khajehpoor; N Samadzadehaghdam; E Eqlimi; M R Deevband
Journal:  J Biomed Phys Eng       Date:  2019-12-01

9.  Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

Authors:  J D López; V Litvak; J J Espinosa; K Friston; G R Barnes
Journal:  Neuroimage       Date:  2013-09-13       Impact factor: 6.556

10.  Temporal stability of functional brain modules associated with human intelligence.

Authors:  Kirsten Hilger; Makoto Fukushima; Olaf Sporns; Christian J Fiebach
Journal:  Hum Brain Mapp       Date:  2019-10-06       Impact factor: 5.038

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  2 in total

1.  The time-varying networks of the wrist extension in post-stroke hemiplegic patients.

Authors:  Fali Li; Lin Jiang; Yangsong Zhang; Dongfeng Huang; Xijun Wei; Yuanling Jiang; Dezhong Yao; Peng Xu; Hai Li
Journal:  Cogn Neurodyn       Date:  2021-11-02       Impact factor: 3.473

2.  Dynamic networks of P300-related process.

Authors:  Qin Tao; Lin Jiang; Fali Li; Yuan Qiu; Chanlin Yi; Yajing Si; Cunbo Li; Tao Zhang; Dezhong Yao; Peng Xu
Journal:  Cogn Neurodyn       Date:  2022-01-10       Impact factor: 3.473

  2 in total

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