TITLE
Network Mechanisms of Clinical Response to Transcranial Magnetic Stimulation in Posttraumatic Stress Disorder and Major Depressive Disorder
SOURCE
Biological Psychiatry. 83(3):263-272, 2018 02 01.
AUTHORS
Philip NS; Barredo J; van ‘t Wout-Frank M; Tyrka AR; Price LH; Carpenter LL.
BACKGROUND
Repetitive transcranial magnetic stimulation (TMS) therapy can modulate pathological neural network functional connectivity in major depressive disorder (MDD). Posttraumatic stress disorder is often co-morbid with MDD, and symptoms of both disorders can be alleviated with TMS therapy. This is the first study to evaluate TMS-associated changes in connectivity in patients with co-morbid posttraumatic stress disorder and MDD.
METHODS
Resting-state functional connectivity magnetic resonance imaging was acquired before and after TMS therapy in 33 adult outpatients in a prospective open trial. TMS at 5 Hz was delivered, in up to 40 daily sessions, to the left dorsolateral prefrontal cortex. Analyses used a priori seeds relevant to TMS, posttraumatic stress disorder, or MDD (subgenual anterior cingulate cortex [sgACC], left dorsolateral prefrontal cortex, hippocampus, and basolateral amygdala) to identify imaging predictors of response and to evaluate clinically relevant changes in connectivity after TMS, followed by leave-one-out cross-validation. Imaging results were explored using data-driven multivoxel pattern activation.
RESULTS
More negative pretreatment connectivity between the sgACC and the default mode network predicted clinical improvement, as did more positive amygdala-to-ventromedial prefrontal cortex connectivity. After TMS, symptom reduction was associated with reduced connectivity between the sgACC and the default mode network, left dorsolateral prefrontal cortex, and insula, and reduced connectivity between the hippocampus and the salience network. Multivoxel pattern activation confirmed seed-based predictors and correlates of treatment outcomes.
CONCLUSIONS
These results highlight the central role of the sgACC, default mode network, and salience network as predictors of TMS response and suggest their involvement in mechanisms of action. Furthermore, this work indicates that there may be network-based biomarkers of clinical response relevant to these commonly co-morbid disorders.
