The neurophysiology of recurrence risk in depression

To develop novel prophylactic treatments and decision support systems, there is an urgent need to understand the pathophysiology and predict risk of recurrence in major depressive disorder (MDD). Using fMRI, we have previously found that balanced connectivity across fronto-temporo-subcortical networks guards against overgeneralised self-blame and recurrence in MDD.

Aim:
Functional MRI, due to its slower timescale, is poorly suited to measure temporal binding in neural networks which has been shown to be of major importance to conscious experience. Electroencephalography (EEG) is an affordable method with higher temporal resolution and therefore ideally suited to investigate temporal dynamics and binding. The proposed PhD project will investigate this intriguing question.