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Title: | EEG-based functional connectivity analysis of brain abnormalities: A systematic review study |
Authors: | Khaleghi, N Hashemi, S Peivandi, M Zafarmandi Ardabili, S Behjati, M Sheykhivand, S Danishvar, S |
Keywords: | electroencephalogram;functional connectivity;brain abnormalities |
Issue Date: | 21-Mar-2024 |
Publisher: | Elsevier |
Citation: | Khaleghi, N. et al. (2024) 'EEG-based functional connectivity analysis of brain abnormalities: A systematic review study', Informatics in Medicine Unlocked, 47, 101476, pp. 1 - 41. doi: 10.1016/j.imu.2024.101476. |
Abstract: | Several imaging modalities and many signal recording techniques have been used to study the brain activities. Significant advancements in medical device technologies like electroencephalographs have provided conditions for recording neural information with high temporal resolution. These recordings can be used to calculate the connections between different brain areas. It has been proved that brain abnormalities affect the brain activity in different brain regions and the connectivity patterns between them are changed as a result. This paper studies the electroencephalogram (EEG) functional connectivity methods and investigates the impacts of brain abnormalities on brain functional connectivities. The effects of different brain abnormalities including stroke, depression, emotional disorders, epilepsy, attention deficit hyperactivity disorder (ADHD), autism, and Alzheimer's disease on functional connectivity of the EEG recordings have been explored in this study. The EEG-based metrics and network properties of different brain abnormalities have been discussed to present a comparison of the connectivities affected by each abnormality. Also, the effects of therapy and medical intake on the EEG functional connectivity network of each abnormality have been reviewed. |
URI: | https://bura.brunel.ac.uk/handle/2438/28776 |
DOI: | https://doi.org/10.1016/j.imu.2024.101476 |
Other Identifiers: | ORCiD: Sebelan Danishvar https://orcid.org/0000-0002-8258-0437 101476 |
Appears in Collections: | Dept of Computer Science Research Papers |
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