Brain functional and effective connectivity based on electroencephalography recordings: a review

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dc.contributor.authorCao, Jun
dc.contributor.authorZhao, Yifan
dc.contributor.authorShan, Xiaocai
dc.contributor.authorWei, Hua-Liang
dc.contributor.authorGuo, Yuzhu
dc.contributor.authorChen, Liangyu
dc.contributor.authorErkoyuncu, John Ahmet
dc.contributor.authorSarrigiannis, Ptolemaios Georgios
dc.date.accessioned2021-10-22T09:56:26Z
dc.date.available2021-10-22T09:56:26Z
dc.date.issued2021-10-20
dc.description.abstractFunctional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional mechanism. Many recent studies on electroencephalography (EEG) have been focusing on modeling and estimating brain connectivity due to increasing evidence that it can help better understand various brain neurological conditions. However, there is a lack of a comprehensive updated review on studies of EEG-based brain connectivity, particularly on visualization options and associated machine learning applications, aiming to translate those techniques into useful clinical tools. This article reviews EEG-based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric or nonparametric, time-based, and frequency-based or time-frequency-based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics, and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.en_UK
dc.identifier.citationCao J, Zhao Y, Shan X, et al., (2022) Brain functional and effective connectivity based on electroencephalography recordings: a review. Human Brain Mapping, Volume 43, Issue 2, February 2022, pp. 860-879en_UK
dc.identifier.issn1065-9471
dc.identifier.urihttps://doi.org/10.1002/hbm.25683
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/17192
dc.language.isoenen_UK
dc.publisherWileyen_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectartificial intelligenceen_UK
dc.subjectbrain associationen_UK
dc.subjectelectroencephalogramen_UK
dc.subjectmachine learningen_UK
dc.subjectsurveyen_UK
dc.titleBrain functional and effective connectivity based on electroencephalography recordings: a reviewen_UK
dc.typeArticleen_UK

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