Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/64756
Title: Differences in EEG Functional Connectivity in the Dorsal and Ventral Attentional and Salience Networks Across Multiple Subtypes of Depression
Contributor(s): Evans, Ian D  (author)orcid ; Sharpley, Christopher F  (author)orcid ; Bitsika, Vicki  (author)orcid ; Vessey, Kirstan A  (author)orcid ; Williams, Rebecca J  (author)orcid ; Jesulola, Emmanuel  (author); Agnew, Linda L  (author)orcid 
Publication Date: 2025-02-01
Open Access: Yes
DOI: 10.3390/app15031459
Handle Link: https://hdl.handle.net/1959.11/64756
Abstract: 

Depression remains one of the most widespread and costly mental disorders, with the current first-line treatment efficacy of about a third, possibly due to its heterogeneous nature. Consequently, there is a need to identify reliable biomarkers for specific subtypes of depression, particularly neurological signatures that may help with targeted treatments. This study aimed to explore the connectivity between two important networks in the brain: the dorsal and ventral attention networks and the salience network, to determine their potential as biomarkers of depression subtypes. From resting electroencephalogram (EEG) data collected on 54 males and 46 females aged between 18 and 75 yr (M = 33 yr), functional network connectivity data were examined for their relationships with four depression subtypes. Beta and gamma wave connectivity was significantly associated with Anhedonia and Cognitive depression subtypes across and within all three networks while no significant results were found for alpha wave activity connectivity, and only one result was found for either the Mood or Somatic depression subtypes. In conclusion, these results provide further support for the concept of depression as heterogeneous rather than homogeneous and identify the novel neurophysiological signatures of two depression subtypes.

Publication Type: Journal Article
Source of Publication: Applied Sciences, 15(3), p. 1-13
Publisher: Universitatea Politehnica din Bucuresti, Department of Mathematics
Place of Publication: Romania
ISSN: 1454-5101
Fields of Research (FoR) 2020: 3209 Neurosciences
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Education
School of Science and Technology

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