Klaver, Casper (2021) Scanning for Depression: The effect of functional connectivity on major depressive disorder treatment choice. Master's Thesis / Essay, Biomedical Sciences.
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Abstract
Major depressive disorder (MDD) is still not well treatable. Symptoms disappear in only 37% of the patients after a first treatment course, and only 67% of the patients see their symptoms disappear overall. Functional connectivity, defined as the similarity of activation patterns between brain areas, has been shown to be disrupted in MDD patients. The triple network model of dysfunction proposes that in MDD patients, the default mode network (DMN) activity is increased while the activities of the central executive network (CEN) and the salience network (SN) are decreased. These activity changes decrease the functional connectivity between these networks. Yet, as MDD is a very heterogeneous disorder, it is likely different across patients. These differences could tell something about treatment response. Could functional connectivity help select the right medication for the patient? Though, functional connectivity is not able to tell anything about the etiology of the disease in the patient, differences in functional connectivity have been shown to lead to differences in antidepressant response. Due to inconsistencies of functional connectivity, focusing on specific brain areas will not give great predictions regarding treatment response. Recent computational models, however, use functional connectivity to create a “functional connectivity signature” for every patient, and can make moderately well predictions regarding not just treatment response, but also certain risks like su
| Item Type: | Thesis (Master's Thesis / Essay) |
|---|---|
| Supervisor name: | Havekes, R. |
| Degree programme: | Biomedical Sciences |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 20 Jul 2021 12:59 |
| Last Modified: | 20 Jul 2021 13:00 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/25350 |
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