Efficacy of Transcranial Magnetic Stimulation Targets for Depression Is Related to Intrinsic Functional Connectivity with the Subgenual Cingulate

Abstract

BACKGROUND Transcranial magnetic stimulation (TMS) to the left dorsal-lateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression. However the antidepressant mechanism remains unknown and its therapeutic efficacy remains limited. Recent data suggests that some left DLPFC targets are more effective than others, however the reasons for this heterogeneity and how to capitalize on this information remain unclear. METHODS Intrinsic (resting state) fMRI data from 98 normal subjects were used to compute functional connectivity with various left DLPFC TMS targets employed in the literature. Differences in functional connectivity related to differences in previously reported clinical efficacy were identified. This information was translated into a connectivity-based targeting strategy to identify optimized left DLPFC TMS coordinates. Results in normal subjects were tested for reproducibility in an independent cohort of 13 patients with depression. RESULTS Differences in functional connectivity were related to previously reported differences in clinical efficacy across a distributed set of cortical and limbic regions. DLPFC TMS sites with better clinical efficacy were more negatively correlated (anticorrelated) with the subgenual cingulate. Optimum connectivity-based stimulation coordinates were identified in BA46. Results were reproducible in patients with depression. CONCLUSIONS Reported antidepressant efficacy of different left DLPFC TMS sites is related to the anticorrelation of each site with the subgenual cingulate, potentially lending insight into the antidepressant mechanism of TMS and suggesting a role for intrinsically anticorrelated networks in depression. These results can be translated into a connectivity-based targeting strategy for focal brain stimulation that might be used to optimize clinical response.

A novel concurrent TMS‐fMRI method to reveal propagation patterns of prefrontal magnetic brain stimulation

“…This concept can potentially be used to predict treatment outcome or to increase treatment efficacy of repetitive stimulation of the DLPFC in MDD. For example, by targeting treatment at the functional region near the DLPFC that leads to individual sgACC activation, assuming the pathway from prefrontal cortex to sgACC is the mechanism of action of the antidepressant effect of rTMS, as has been suggested (Baeken et al, 2014; Fox et al, 2012). In this way, future studies can investigate whether propagation of TMS‐induced activity to sgACC is an accurate predictor of a clinical response to rTMS treatment of the DLPFC in a clinical population of patients with MDD.…”

“…This can be done by using a patient's individual response to TMS to optimize the effects after subsequent treatment with repetitive stimulation. More specifically, identification of the propagation patterns can reveal whether TMS‐induced activity evoked at the DLPFC has the ability to propagate to the sgACC, and potentially modulate the activity in the sgACC (Fox et al, 2012). …”

Imaging human brain networks to improve the clinical efficacy of non-invasive brain stimulation

“…Repetitive TMS has also been used to modulate the activity of local brain regions implicated in a range of psychiatric and neurological disorders. For example, rTMS-induced enhancement or reduction of neural activity within the left dorsolateral prefrontal cortex (DLPFC) can reduce symptoms of depression, schizophrenia, anxiety, and post-traumatic stress disorder (Prikryl et al, 2007;Fitzgerald et al, 2009;Fox et al, 2012;Balconi and Ferrari, 2013). Of note, though, is that a recent meta-analysis has suggested that the efficacy of this local approach is probably suboptimal (Lefaucheur et al, 2014).…”

“…Although several reviews have alluded to the effects of NIBS propagating to distant regions via axonal connectivity (Lefaucheur et al, 2014;Liew et al, 2014;Li et al, 2015), they have not considered the consequence of these aspects in the clinical domain. An often overlooked factor affecting the effectiveness of NIBS is the optimal targeting of underlying neural networks associated with the clinical condition (Fox et al, 2012). For instance, the efficacy of TMS in the treatment of depression is influenced by the precise location of stimulation within the DLPFC.…”

“…For instance, the efficacy of TMS in the treatment of depression is influenced by the precise location of stimulation within the DLPFC. The region with the highest efficacy was a region with anticorrelated activity between DLPFC and the subgenual cingulate (Fox et al, 2012). Further, several studies have now investigated how each of the different forms…”