A Causal Neural Network-Level Understanding of Depression and its Treatment through Concurrent TMS and fMRI

Amit Etkin, M.D., Ph.D.

Stanford University School of Medicine

Grant Program:

David Mahoney Neuroimaging Program

Funded in:

September 2011, for 3 years

Funding Amount:


Lay Summary

Combined fMRI and TMS may show how depression is caused and treated at the neural network level

This study in depressed patients will examine how depression may be produced by malfunctioning interactions of two neural networks and how a non-invasive treatment called repetitive transcranial magnetic stimulation (rTMS) intervenes to improve outcomes.

Only about 50 percent of people with depression are successfully treated with available therapies, due in large part to our current lack of understanding of the neurological bases of depression.  Prior fMRI studies have implicated low activity levels in some neural networks in several brain regions. These findings, for instance, prompted testing of deep brain stimulation (DBS) for severely depressed patients. For less seriously ill patients, clinicians are using non-invasive rTMS. This technique manipulates activity in specific brain areas through use of electrodes placed on the scalp which are activated by a magnet placed above the patient’s head. But, scientists do not know exactly how rTMS works, for whom it is most likely to work, or how best to target it for optimum results. Stanford investigators recently found fMRI evidence that depression may result from abnormal interactions between two neural networks: 1) the “executive control” network, involved in cognitive functions such as focused attention and judgment; and 2) the “default mode” network, involved in self-attention and autobiographical memory. Depressed patients performing a task requiring attention had low activation in the “executive control” network and high default-mode network activation. Healthy people demonstrated just the opposite. Moreover, healthy people at rest have reciprocal changes in these two networks, suggesting that one network normally inhibits the other depending upon whether thoughts are focused outward or inward.

The investigators hypothesize that this inhibitory relationship is altered in people with depression. They also hypothesize that rTMS may achieve its clinical effectiveness by stimulating the region containing the executive control network.  They will test these two related but independent hypotheses in 40 patients with depression and 20 healthy volunteer participants. First, they will perform fMRI at baseline in all 60 study participants to identify the executive control and default networks. Then, they will take fMRI scans while using TMS stimulation to target these areas. This will enable them to examine the causal and directional interactions between these two networks. Thereafter, the 40 depressed patients will be randomized to receive either rTMS treatment or sham rTMS (placebo) for four weeks. Following treatment, patients will receive an fMRI scan during TMS stimulation, to assess the impact of the treatment on the two network’s interactions, and correlate the findings with clinical outcomes. They anticipate that rTMS will normalize these network interactions.

Significance: This study may reveal a causal network-level understanding of depression and its treatment, providing the potential to target rTMS optimally in individual patients, and to validate other treatments according to their effects on the networks’ interactions.