Repetitive transcranial magnetic stimulation (rTMS) in autism spectrum disorder: protocol for a multicentre randomised controlled clinical trial

Introduction There are no well-established biomedical treatments for the core symptoms of autism spectrum disorder (ASD). A small number of studies suggest that repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technique, may improve clinical and cognitive outcomes in ASD. We describe here the protocol for a funded multicentre randomised controlled clinical trial to investigate whether a course of rTMS to the right temporoparietal junction (rTPJ), which has demonstrated abnormal brain activation in ASD, can improve social communication in adolescents and young adults with ASD. Methods and analysis This study will evaluate the safety and efficacy of a 4-week course of intermittent theta burst stimulation (iTBS, a variant of rTMS) in ASD. Participants meeting criteria for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition ASD (n=150, aged 14–40 years) will receive 20 sessions of either active iTBS (600 pulses) or sham iTBS (in which a sham coil mimics the sensation of iTBS, but no active stimulation is delivered) to the rTPJ. Participants will undergo a range of clinical, cognitive, epi/genetic, and neurophysiological assessments before and at multiple time points up to 6 months after iTBS. Safety will be assessed via a structured questionnaire and adverse event reporting. The study will be conducted from November 2020 to October 2024. Ethics and dissemination The study was approved by the Human Research Ethics Committee of Monash Health (Melbourne, Australia) under Australia’s National Mutual Acceptance scheme. The trial will be conducted according to Good Clinical Practice, and findings will be written up for scholarly publication. Trial registration number Australian New Zealand Clinical Trials Registry (ACTRN12620000890932)

ARTIST: a fully automated artifact rejection algorithm for single-pulse TMS-EEG data

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.Wei Wu, Corey J. Keller, Nigel C. Rogasch, Parker Longwell, Emmanuel Shpigel, Camarin E. Rolle, Amit Etki

Impact of different intensities of intermittent theta burst stimulation on the cortical properties during TMS-EEG and working memory performance

Intermittent theta burst stimulation (iTBS) is a noninvasive brain stimulation technique capable of increasing cortical excitability beyond the stimulation period. Due to the rapid induction of modulatory effects, prefrontal application of iTBS is gaining popularity as a therapeutic tool for psychiatric disorders such as depression. In an attempt to increase efficacy, higher than conventional intensities are currently being applied. The assumption that this increases neuromodulatory may be mechanistically false for iTBS. This study examined the influence of intensity on the neurophysiological and behavioural effects of iTBS in the prefrontal cortex. Sixteen healthy participants received iTBS over prefrontal cortex at either 50, 75 or 100% resting motor threshold in separate sessions. Single-pulse TMS and concurrent electroencephalography (EEG) was used to assess changes in cortical reactivity measured as TMS-evoked potentials and oscillations. The n-back task was used to assess changes in working memory performance. The data can be summarised as an inverse U-shape relationship between intensity and iTBS plastic effects, where 75% iTBS yielded the largest neurophysiological changes. Improvement in reaction time in the 3-back task was supported by the change in alpha power, however, comparison between conditions revealed no significant differences. The assumption that higher intensity results in greater neuromodulatory effects may be false, at least in healthy individuals, and should be carefully considered for clinical populations. Neurophysiological changes associated with working memory following iTBS suggest functional relevance. However, the effects of different intensities on behavioural performance remain elusive in the present healthy sample.Sung Wook Chung, Nigel C. Rogasch, Kate E. Hoy, Caley M. Sullivan, Robin F.H. Cash, Paul B. Fitzgeral

Differentiating responders and non-responders to rTMS treatment for depression after one week using resting EEG connectivity measures

BACKGROUND:Non-response to repetitive transcranial magnetic stimulation (rTMS) treatment for depression is costly for both patients and clinics. Simple and cheap methods to predict response would reduce this burden. Resting EEG measures differentiate responders from non-responders, so may have utility for response prediction. METHODS:Fifty patients with treatment resistant depression and 21 controls had resting electroencephalography (EEG) recorded at baseline (BL). Patients underwent 5-8 weeks of rTMS treatment, with EEG recordings repeated at week 1 (W1). Forty-two participants had valid BL and W1 EEG data, and 12 were responders. Responders and non-responders were compared at BL and W1 in measures of theta (4-8 Hz) and alpha (8-13 Hz) power and connectivity, frontal theta cordance and alpha peak frequency. Control group comparisons were made for measures that differed between responders and non-responders. A machine learning algorithm assessed the potential to differentiate responders from non-responders using EEG measures in combination with change in depression scores from BL to W1. RESULTS:Responders showed elevated theta connectivity across BL and W1. No other EEG measures differed between groups. Responders could be distinguished from non-responders with a mean sensitivity of 0.84 (p = 0.001) and specificity of 0.89 (p = 0.002) using cross-validated machine learning classification on the combination of all EEG and mood measures. LIMITATIONS:The low response rate limited our sample size to only 12 responders. CONCLUSION:Resting theta connectivity at BL and W1 differ between responders and non-responders, and show potential for predicting response to rTMS treatment for depression.N.W. Bailey, K.E. Hoy, N.C. Rogasch, R.H. Thomson, S. McQueen, D. Elliot, C.M. Sullivan, B.D. Fulcher, Z.J. Daskalakis, P.B. Fitzgeral

Responders to rTMS for depression show increased fronto-midline theta and theta connectivity compared to non-responders

Background: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, but only some individuals respond. Predicting response could reduce patient and clinical burden. Neural activity related to working memory (WM) has been related to mood improvements, so may represent a biomarker for response prediction. Primary Hypotheses: We expected higher theta and alpha activity in responders compared to non-responders to rTMS. Methods: Fifty patients with treatment resistant depression and twenty controls performed a WM task while electroencephalography (EEG) was recorded. Patients underwent 5-8 weeks of rTMS treatment, repeating the EEG at week 1 (W1). Of the 39 participants with valid WM-related EEG data from baseline and W1, 10 were responders. Comparisons between responders and non-responders were made at baseline and W1 for measures of theta (4-8 Hz), upper alpha (10-12.5 Hz), and gamma (30-45 Hz) power, connectivity, and theta-gamma coupling. The control group's measures were compared to the depression group's baseline measures separately. Results: Responders showed higher levels of WM-related fronto-midline theta power and theta connectivity compared to non-responders at baseline and W1. Responder's fronto-midline theta power and connectivity was similar to controls. Responders also showed an increase in gamma connectivity from baseline to W1, with a concurrent improvement in mood and WM reaction times. An unbiased combination of all measures provided mean sensitivity of 0.90 at predicting responders and specificity of 0.92 in a predictive machine learning algorithm. Conclusion: Baseline and W1 fronto-midline theta power and theta connectivity show good potential for predicting response to rTMS treatment for depression.N.W. Bailey, K.E. Hoy, N.C. Rogasch, R.H. Thomson, S. McQueen, D. Elliot, C.M. Sullivan, B.D. Fulcher, Z.J. Daskalakis, P.B. Fitzgeral

The influence of endogenous estrogen on high-frequency prefrontal transcranial magnetic stimulation

Background: The use of repetitive transcranial magnetic stimulation (rTMS) as both therapeutic and experimental tools has grown enormously over the past decade. However, variability in response to rTMS is one challenge that remains to be solved. Estrogen can impact neural plasticity and may also affect plastic changes following rTMS. The present study investigated whether estrogen levels influence the neurophysiological effects of high-frequency (HF) rTMS in the left dorsolateral prefrontal cortex (DLPFC). Hypothesis: It was hypothesised that individuals with higher endogenous estrogen would demonstrate greater rTMS-induced changes in cortical reactivity. Methods: 29 healthy adults (15M/14F) received HF-rTMS over left DLPFC. Females attended two sessions, one during a high-estrogen (HE) phase of the menstrual cycle, another during a low-estrogen (LE) phase. Males attended one session. Estrogen level was verified via blood assay. TMS-EEG was used to probe changes in cortical plasticity and comparisons were made using cluster-based permutation statistics and Bayesian analysis. Results: In females, a significant increase in TMS-evoked P60 amplitude, and decrease in N45, N100 and P180 amplitudes was observed during HE. A less pervasive pattern of change was observed during LE. No significant changes in TEPs were seen in males. Between-condition comparisons revealed higher likelihood of the change in N100 and/or P180 being larger in females during HE compared to both females during LE and males. Conclusions: These preliminary findings indicate that a greater neuroplastic response to prefrontal HF-rTMS is seen in women when estrogen is at its highest compared to men, suggesting that endogenous estrogen levels contribute to variability in response to HF-rTMS.Sung Wook Chung, Cassandra J. Thomson, Susan Lee, Roisin N. Worsley, Nigel C. Rogasch, Jayashri Kulkarni, Richard H. Thomson, Paul B. Fitzgerald, Rebecca A. Segrav