Accelerated Repetitive Transcranial Magnetic Stimulation to Treat Major Depression: The Past, Present, and Future.

Repetitive transcranial magnetic stimulation (rTMS) is an effective and evidence-based therapy for treatment-resistant major depressive disorder. A conventional course of rTMS applies 20-30 daily sessions over 4-6 weeks. The schedule of rTMS delivery can be accelerated by applying multiple stimulation sessions per day, which reduces the duration of a treatment course with a predefined number of sessions. Accelerated rTMS reduces time demands, improves clinical efficiency, and potentially induces faster onset of antidepressant effects. However, considerable heterogeneity exists across study designs. Stimulation protocols vary in parameters such as the stimulation target, frequency, intensity, number of pulses applied per session or over a course of treatment, and duration of intersession intervals. In this article, clinician-researchers and neuroscientists who have extensive research experience in accelerated rTMS synthesize a consensus based on two decades of investigation and development, from early studies ("Past") to contemporaneous theta burst stimulation, a time-efficient form of rTMS gaining acceptance in clinical settings ("Present"). We propose descriptive nomenclature for accelerated rTMS, recommend avenues to optimize therapeutic and efficiency potential, and suggest using neuroimaging and electrophysiological biomarkers to individualize treatment protocols ("Future"). Overall, empirical studies show that accelerated rTMS protocols are well tolerated and not associated with serious adverse effects. Importantly, the antidepressant efficacy of accelerated rTMS appears comparable to conventional, once daily rTMS protocols. Whether accelerated rTMS induces antidepressant effects more quickly remains uncertain. On present evidence, treatment protocols incorporating high pulse dose and multiple treatments per day show promise and improved efficacy.

Personalizing Repetitive Transcranial Magnetic Stimulation Parameters for Depression Treatment Using Multimodal Neuroimaging.

Repetitive transcranial magnetic stimulation (rTMS) is a tool that can be used to administer treatment for neuropsychiatric disorders such as major depressive disorder, although the clinical efficacy is still rather modest. Overly general stimulation protocols that consider neither patient-specific depression symptomology nor individualized brain characteristics, such as anatomy or structural and functional connections, may be the cause of the high inter- and intraindividual variability in rTMS clinical responses. Multimodal neuroimaging can provide the necessary insights into individual brain characteristics and can therefore be used to personalize rTMS parameters. Optimal coil positioning should include a three-step process: 1) identify the optimal (indirect) target area based on the exact symptom pattern of the patient; 2) derive the cortical (direct) target location based on functional and/or structural connectomes derived from functional and diffusion magnetic resonance imaging data; and 3) determine the ideal coil position by computational modeling, such that the electric field distribution overlaps with the cortical target. These TMS-induced electric field simulations, derived from anatomical and diffusion magnetic resonance imaging data, can be further applied to compute optimal stimulation intensities. In addition to magnetic resonance imaging, electroencephalography can provide complementary information regarding the ongoing brain oscillations. This information can be used to determine the optimal timing and frequency of the stimuli. The heightened benefits of these personalized stimulation approaches are logically reasoned, but speculative. Randomized clinical trials will be required to compare clinical responses from standard rTMS protocols to personalized protocols. Ultimately, an optimized clinical response may result from precision protocols derived from combinations of personalized stimulation parameters.

EEG Functional Connectivity is a Weak Predictor of Causal Brain Interactions.

In recent years there has been an explosion of research evaluating resting-state brain functional connectivity (FC) using different modalities. However, the relationship between such measures of FC and the underlying causal brain interactions has not been well characterized. To further characterize this relationship, we assessed the relationship between electroencephalography (EEG) resting state FC and propagation of transcranial magnetic stimulation (TMS) evoked potentials (TEPs) at the sensor and source level in healthy participants. TMS was applied to six different cortical regions in ten healthy individuals (9 male; 1 female), and effects on brain activity were measured using simultaneous EEG. Pre-stimulus FC was assessed using five different FC measures (Pearson's correlation, mutual information, weighted phase lag index, coherence and phase locking value). Propagation of the TEPs was quantified as the root mean square (RMS) of the TEP voltage and current source density (CSD) at the sensor and source level, respectively. The relationship between pre-stimulus FC and the spatial distribution of TEP activity was determined using a generalized linear model (GLM) analysis. On the group level, all FC measures correlated significantly with TEP activity over the early (15-75 ms) and full range (15-400 ms) of the TEP at the sensor and source level. However, the predictive value of all FC measures is quite limited, accounting for less than 10% of the variance of TEP activity, and varies substantially across participants and stimulation sites. Taken together, these results suggest that EEG functional connectivity studies in sensor and source space should be interpreted with caution.

Indirect frontocingulate structural connectivity predicts clinical response to accelerated rTMS in major depressive disorder

Background: Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD), but its clinical efficacy remains rather modest. One reason for this could be that the propagation of rTMS effects via structural connections from the stimulated area to deeper brain structures (such as the cingulate cortices) is suboptimal. Methods: We investigated whether structural connectivity ­ derived from diffusion MRI data ­ could serve as a biomarker to predict treatment response. We hypothesized that stronger structural connections between the patient-specific stimulation position in the left dorsolateral prefrontal cortex (dlPFC) and the cingulate cortices would predict better clinical outcomes. We applied accelerated intermittent theta burst stimulation (aiTBS) to the left dlPFC in 40 patients with MDD. We correlated baseline structural connectivity, quantified using various metrics (fractional anisotropy, mean diffusivity, tract density, tract volume and number of tracts), with changes in depression severity scores after aiTBS. Results: Exploratory results (p < 0.05) showed that structural connectivity between the patient-specific stimulation site and the caudal and posterior parts of the cingulate cortex had predictive potential for clinical response to aiTBS. Limitations: We used the diffusion tensor to perform tractography. A main limitation was that multiple fibre directions within voxels could not be resolved, which might have led to missing connections in some patients. Conclusion: Stronger structural frontocingular connections may be of essence to optimally benefit from left dlPFC rTMS treatment in MDD. Even though the results are promising, further investigation with larger numbers of patients, more advanced tractography algorithms and classic daily rTMS treatment paradigms is warranted. Clinical trial registration: http://clinicaltrials.gov/show/NCT01832805

Focal application of accelerated iTBS results in global changes in graph measures.

Graph analysis was used to study the effects of accelerated intermittent theta burst stimulation (aiTBS) on the brain's network topology in medication-resistant depressed patients. Anatomical and resting-state functional MRI (rs-fMRI) was recorded at baseline and after sham and verum stimulation. Depression severity was assessed using the Hamilton Depression Rating Scale (HDRS). Using various graph measures, the different effects of sham and verum aiTBS were calculated. It was also investigated whether changes in graph measures were correlated to clinical responses. Furthermore, by correlating baseline graph measures with the changes in HDRS in terms of percentage, the potential of graph measures as biomarker was studied. Although no differences were observed between the effects of verum and sham stimulation on whole-brain graph measures and changes in graph measures did not correlate with clinical response, the baseline values of clustering coefficient and global efficiency showed to be predictive of the clinical response to verum aiTBS. Nodal effects were found throughout the whole brain. The distribution of these effects could not be linked to the strength of the functional connectivity between the stimulation site and the node. This study showed that the effects of aiTBS on graph measures distribute beyond the actual stimulation site. However, additional research into the complex interactions between different areas in the brain is necessary to understand the effects of aiTBS in more detail.