Investigating predictors of response to Transcranial Magnetic Stimulation for the treatment of depression

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Major depressive disorder (MDD) is common, associated with considerable disability and high morbidity and often resistant to treatment with standard approaches (~30% of patients meet standard definitions for treatment resistant depression (TRD)). There is currently an overwhelming need in the community for the development of better and novel treatments for depression. Despite the demand, there are relatively few treatment options available to patients with TRD. One of the only substantially new treatments developed in recent years has been repetitive transcranial magnetic stimulation (rTMS). Despite the considerable bulk of evidence demonstrating that rTMS can be effective in the treatment of depression, a major issue that limits its wider use is that only between 40-50% of patients respond to rTMS treatment. While this is a good response rate in a group of patients with significant depression who have failed to respond to other treatments, participation in rTMS treatment involves a considerable commitment of time and resources (stimulation is usually provided five days per week to outpatients who attend for up to six weeks). It is therefore essential to be able to identify patients who are more or less likely to respond to treatment. This research aims to provide a practical and clinically useful approach to predicting antidepressant response to rTMS treatment. In addition, by providing greater information about the underlying causes of depression and how these interact with treatments, this research may ultimately assist in developing more effective therapies for TRD. This would have a significant impact on the considerable numbers of Australians with depression who have tried standard therapies and yet remain significantly unwell. Therefore the current project aims to use both novel and more established neuroscience methodologies (namely electroencephalogy (EEG), TMS and near infra-red spectroscopy (NIRS)) to investigate whether such techniques can be used to predict response to rTMS treatment in depression.