WHAT DOES ELECTROENCEPHALOGRAM CONNECTIVITY ANALYSIS TELL US ABOUT DEPRESSION?

Islam, Ameer (2021) WHAT DOES ELECTROENCEPHALOGRAM CONNECTIVITY ANALYSIS TELL US ABOUT DEPRESSION? Bachelor's Thesis, Artificial Intelligence.

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Abstract

Previous research has shown that functional connectivity of Electroencephalogram (EEG) between different parts of the brain is somewhat predictive of Major Depressive Disorder (MDD). Apart from the functional connectivity also power in various frequency bands (alpha, delta, theta and beta) has been shown to differ between healthy individuals and MDD patients. Specifically, patients with MDD had a significant increase in the theta, alpha and beta frequency bands compared to healthy controls, in the frontal and occipital regions of the brains. This study aimed to investigate whether there was a difference in the functional connectivity and power spectra between more depressed participants compared to less depressed participants who were ranked on a depression spectrum rather than being separated into healthy controls and MDD patients. In addition, this study focused on frontal brain areas represented through 9 electrodes (FP1, FP2, AF3, AF4, F7, F3, FZ, F4, F8) to examine functional connectivity and power spectra. We examined EEG functional connectivity across the frontal brain area during the resting state using the Phase Lag Index (PLI). In addition to functional connectivity, we examined oscillatory power during the resting state, in the 5 frequency bands ; delta (0.5 to 4Hz); theta (4 to 7Hz); alpha (8 to 12Hz) and beta (13 to 30Hz). The results showed that less depressed individuals had higher frontal theta power than more depressed individuals. All other frequency bands a

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Vugt, M.K. van and Yang, H.
Degree programme:	Artificial Intelligence
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	19 Apr 2021 08:58
Last Modified:	19 Apr 2021 08:58
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/24275

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