AbstractMajor depression and anxiety disorders are debilitating and prevalent conditions, yet current methods for tailoring treatments and predicting treatment response are suboptimal, in part due to a lack of understanding of the biological and behavioural bases of these disorders. Neuroimaging has provided some insights, but this area lacks a well-defined battery of trans-diagnostic psychological measures, and most neuroimaging studies have focused on pharmacological, rather than psychological therapies.
This thesis firstly details meta-analyses of the changes in brain activation and neural predictors of treatment response with psychological therapies to determine whether robust correlates exist currently. Further chapters aimed to pilot novel fMRI and behavioural methods in patients with anxiety and depression. Firstly, a human translation of a rodent task to measure fear and anxiety, which had yet to be piloted in patients with affective disorders, despite the relevance of threat-avoidance to these conditions. Secondly, a novel task to measure self-reflection more directly than currently available methods. Thirdly, a new and underutilised method of analysing resting-state data to reveal temporal variability in connectivity.
We were able to demonstrate consistent changes in brain activation associated with psychological therapies across depression and anxiety, though the meta-analyses highlight how far we are from utilising neuroimaging in clinical practice. We did not find significant differences in brain activation on the novel tasks between patients and controls; however, the task relating to self-reflection showed promise as a behavioural measure. We found increased fluctuations in connectivity between default mode network regions considered crucial for the generation of self-reflective thoughts in patients versus controls. We were able to replicate this finding in an independent sample, suggesting the finding is robust.
These results contribute to an understanding of threat sensitivity and self-reflection in affective disorders and provide ideas for future research in to neural biomarkers and behavioural measures for these conditions.
|Date of Award||2018|
|Supervisor||Anthony Cleare (Supervisor) & Adam Perkins (Supervisor)|