Elsevier

NeuroImage

Volume 66, 1 February 2013, Pages 151-160
NeuroImage

Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity

https://doi.org/10.1016/j.neuroimage.2012.10.082Get rights and content

Abstract

Transcranial magnetic stimulation (TMS) to the left dorsolateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression however outcomes vary greatly between patients. We have shown that average clinical efficacy of different left DLPFC TMS sites is related to intrinsic functional connectivity with remote regions including the subgenual cingulate and suggested that functional connectivity with these remote regions might be used to identify optimized left DLPFC targets for TMS. However it remains unclear if and how this connectivity-based targeting approach should be applied at the single-subject level to potentially individualize therapy to specific patients. In this article we show that individual differences in DLPFC connectivity are large, reproducible across sessions, and can be used to generate individualized DLPFC TMS targets that may prove clinically superior to those selected on the basis of group-average connectivity. Factors likely to improve individualized targeting including the use of seed maps and the focality of stimulation are investigated and discussed. The techniques presented here may be applicable to individualized targeting of focal brain stimulation across a range of diseases and stimulation modalities and can be experimentally tested in clinical trials.

Highlights

► There is significant individual variability in the connectivity of the left DLPFC. ► Individual differences in DLPFC connectivity are reproducible across days. ► Individualized TMS targets appear superior to population-based targets. ► Seed maps improve signal/noise compared to small seed regions. ► Individualized targeting is likely of greater benefit with more focal stimulation.

Introduction

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that is showing utility in the treatment of a variety of neurological and psychiatric disorders (Burt et al., 2002, Fregni and Pascual-Leone, 2007, Hallett, 2007). Its most common use involves high-frequency stimulation to the left dorsal lateral prefrontal cortex (DLPFC) for the treatment of depression (George et al., 1995, O'Reardon et al., 2007, Padberg and George, 2009, Pascual-Leone et al., 1996). In the US, the Neuronetics® device and Neurostar protocol are approved by the Food and Drug Administration for some patients with medication-resistant depression. However, the clinical utility of rTMS remains limited by large heterogeneity in clinical response.

One factor known to contribute to this response heterogeneity is differences in the site of stimulation in the left DLPFC (Ahdab et al., 2010, Fitzgerald et al., 2009, Herbsman et al., 2009, Herwig et al., 2001, Padberg and George, 2009). The targeting technique routinely employed in clinical practice, and followed by the FDA approved protocol, is to center the TMS coil at a point 5 cm anterior to the motor cortex measured along the curvature of the scalp. This approach identifies different stimulation sites in different subjects (Ahdab et al., 2010, Herwig et al., 2001) and some sites appear to be more effective than others at producing an antidepressant response (Fitzgerald et al., 2009, Herbsman et al., 2009, Padberg and George, 2009, Paillère Martinot et al., 2010). In an effort to understand why some sites are more effective, we recently used intrinsic (resting state) fMRI to identify differences in functional connectivity between effective and less effective DLPFC stimulation sites at the population level (Fox et al., 2012a). Significant differences in connectivity were seen in a variety of cortical and limbic regions including the subgenual cingulate, a region repeatedly implicated in antidepressant response to a variety of treatment modalities (Drevets et al., 2008, Mayberg, 2009, Mayberg et al., 2005). Specifically, left DLPFC sites which when targeted with TMS leads to greater antidepressant effects, showed a stronger negative correlation (anticorrelation) with the subgenual. Based on these findings, we proposed a connectivity-based targeting strategy for TMS and used this technique to identify theoretically optimal TMS target coordinates in the left DLPFC at the population level (Fox et al., 2012a).

An important advantage of this connectivity-based targeting strategy is that it might be scaled from the population level down to the level of single subjects to tailor treatment to individual patients. The DLPFC varies greatly between individuals on a histological basis (Rajkowska and Goldman-Rakic, 1995) thus the population-average TMS coordinates might be suboptimal for many patients. However individualized targeting will be associated with an inherent worsening of signal to noise that could overwhelm any benefit of accounting for individual differences. For example, targeting a population-average focus of hypometabolism in the left DLPFC with TMS appears superior to the standard 5 cm technique (Fitzgerald et al., 2009), however three separate studies aiming to target individualized foci of hypometabolism failed to provide clinical benefit (Garcia-Toro et al., 2006, Herwig et al., 2003a, Paillère Martinot et al., 2010). In fMRI, the subgenual is a region with poor signal to noise ratio (Ojemann et al., 1997) and intrinsic anticorrelations may be less reproducible than positive correlations (Shehzad et al., 2009). It therefore remains unclear if connectivity-based targeting can identify individualized TMS sites in the DLPFC that are sufficiently robust and reproducible to potentially be used in the treatment of depression.

In the current article we show that individual differences in DLPFC connectivity are large, reproducible across scanning sessions, and can be translated into individualized TMS targets on the cortical surface. Further, we identify factors likely to improve individualized targeting such as the use of seed maps and the focality of stimulation.

Section snippets

Subjects and data collection

This study utilized three independent datasets, each of which was used for a particular set of analyses (Fig. 1). Datasets 1 and 2 have been used in prior published articles (Fox et al., 2012a, Van Dijk et al., 2012, Yeo et al., 2011) and were not collected specifically for the present paper. However these prior articles investigated different experimental questions than those investigated in the current article and no part of the present report overlaps with prior published findings. Dataset 3

Results

Functional connectivity was computed with three seed regions/seed maps to identify candidate TMS targets in the left DLPFC (Fig. 2). Regardless of whether one used the small subgenual seed region (Fig. 2A), the full subgenual-based seed map (Fig. 2B), or the efficacy-based seed map (Fig. 2C), a clear anticorrelated area was identified at the group level (black circles). Peak MNI coordinates for these anticorrelations for the three group maps are (− 42, 38, 34), (− 42, 44, 26), and (− 38, 44, 26)

Discussion

There are several novel results in the present paper important for successful individualized targeting of TMS to the DLPFC based on functional connectivity. First, individual differences in DLPFC connectivity are large and reproducible across sessions. Second, TMS targets can be selected based on these individual differences and have the potential to be clinically superior to targets selected on the basis of a group map. Finally, individualized targeting might be improved through the use of a

Conclusions

There is significant individual variability in the connectivity of the left DLPFC. This variability is stable across scanning sessions and can be used to generate individualized and reproducible TMS targets. Seed maps demonstrate more stability than a small subgenual seed region and may be an effective technique for improving signal to noise in single subject functional connectivity analyses. Finally, the more focal the stimulation field, the greater the benefit likely to come from

Acknowledgments

We thank the Brain Genomics Superstruct Project for contributing data and David Alsop for assistance with MRI acquisition and sequence optimization for the depression patients. MDF was supported by NIH grant R25NS065743 and HL by NIH grant K25NS069805. APL serves on the scientific advisory boards for Nexstim, Neuronix, Starlab Neuroscience, Neuroelectrics, Neosync, and Novavision, and is listed as inventor in issued patents and patent applications on the real-time integration of transcranial

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