Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/19742
Title: Systematic Review of the Literature, and an Investigation of the Roles of Severity, Gender and Cerebral Sites, in the relationship Between Alpha Electroencephalographic Asymmetry and Depression
Contributor(s): Jesulola, Emmanuel Aderemi (author); Wilson, Peter (supervisor)orcid ; Agnew, Linda (supervisor)orcid ; Sharpley, Christopher (supervisor)orcid 
Conferred Date: 2016
Copyright Date: 2016
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/19742
Abstract: The approach-withdrawal model of depression hypothesizes that depression is characterized by: (i) behavioural withdrawal from negative aversive stimuli (which is associated with increased activation of the right frontal lobe) and (ii) reduced interaction with positive pleasant stimuli (which is evidenced by reduced activation of the left frontal lobe). Therefore, depressed individuals show greater activation in the right vs the left frontal lobes. However, experimental findings in this field of research have shown some inconsistencies in depressed participants. To investigate these inconsistencies, this thesis focused on two tasks. First, a comprehensive review of the literature on the occurrence of alpha EEG asymmetry in depression was undertaken. From this, three important issues which affect the occurrence of alpha EEG asymmetry were identified vis-à-vis the roles of: (i) depression severity, (ii) gender, and (iii) cerebral locations where alpha asymmetry occurs (i.e., frontal, temporal, parietal and occipital sites). Therefore, the second section of this thesis comprises an investigation of the relationship between alpha EEG asymmetry and these three issues.
Publication Type: Thesis Doctoral
Field of Research Codes: 110903 Central Nervous System
Rights Statement: Copyright 2016 - Emmanuel Aderemi Jesulola
Open Access Embargo: 2017-10-23
HERDC Category Description: T2 Thesis - Doctorate by Research
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Appears in Collections:School of Science and Technology
Thesis Doctoral

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