Approaches to the Use of Graph Theory to Study the Human EEG in Health and Cerebral Pathology

The information content of EEG recordings, which are widely used and important for assessing the functional activity of the brain, is significantly increased by the use of mathematical analysis, where an important place is occupied by the spatial synchronization characteristic, i.e., the functional...

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Bibliographic Details
Published in:Neuroscience and behavioral physiology 2023-03, Vol.53 (3), p.381-398
Main Authors: Vigasina, K. D., Proshina, E. A., Gotovtsev, P. M., Sharova, E. V., Bordiug, V. A., Masherov, E. L., Knyazev, G. G.
Format: Article
Language:English
Subjects:
Behavioral Sciences
Biomedical and Life Sciences
Biomedicine
Brain architecture
EEG
Electroencephalography
Localization
Neural networks
Neurobiology
Neuroimaging
Neurosciences
Synchronization
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Summary:The information content of EEG recordings, which are widely used and important for assessing the functional activity of the brain, is significantly increased by the use of mathematical analysis, where an important place is occupied by the spatial synchronization characteristic, i.e., the functional connectivity of biopotentials (based on correlation and coherence analysis, phase synchronization, etc.). The success of neuroimaging methods in recent years has not only confirmed the significance of this indicator, but has also contributed to improvements in approaches to its statistical evaluation and visualization. Graph theory (GT) is a promising method for analyzing the neural network organization of the brain. Its advantages are that it provides a visual description of the entire structure of the network and its individual components, as well as defining the relationships between them. The purpose of this review is to present approaches to the application of graph theory and the potentials of this method based on the analysis of published data. We present general information on the areas of application of GT, address the most common and informative metrics, and provide recommendations for selecting software. Modifications of GT analysis of the EEG are described: without primary localization of the generation sources of EEG components and with their localization. Examples of the effective use of graph theory analysis of the electroencephalogram of the healthy and diseased brain are given.
ISSN:0097-0549
1573-899X
DOI:10.1007/s11055-023-01437-1