Large-scale analysis of interindividual variability in theta-burst stimulation data: Results from the ‘Big TMS Data Collaboration’ - Corp, Daniel T.; Bereznicki, Hannah G.K.; Clark, Gillian M.; Youssef, George J.; Fried, Peter J.; Jannati, Ali; Davies, Charlotte B.; Gomes-Osman, Joyce; Stamm, Julie; Chung, Sung Wook; Bowe, Steven J.; Rogasch, Nigel C.; et al. (Brain stimulation, 2020)
Many studies have attempted to identify the sources of interindividual variability in response to theta-burst stimulation (TBS). However, these studies have been limited by small sample sizes, leading to conflicting results. This study brought together over 60 TMS researchers to form the ‘Big TMS Data Collaboration’, and create the largest known sample of individual participant TBS data to date. The goal was to enable a more comprehensive evaluation of factors driving TBS response variability. 118 corresponding authors of TMS studies were emailed and asked to provide deidentified individual TMS data. Mixed-effects regression investigated a range of individual and study level variables for their contribution to iTBS and cTBS response variability. 430 healthy participants’ TBS data was pooled across 22 studies (mean age = 41.9; range = 17–82; females = 217). Baseline MEP amplitude, age, target muscle, and time of day significantly predicted iTBS-induced plasticity. Baseline MEP amplitude and timepoint after TBS significantly predicted cTBS-induced plasticity. This is the largest known study of interindividual variability in TBS. Our findings indicate that a significant portion of variability can be attributed to the methods used to measure the modulatory effects of TBS. We provide specific methodological recommendations in order to control and mitigate these sources of variability. •430 healthy participants’ theta-burst stimulation data was pooled across 22 studies.•Individual participant data was analysed using mixed-effects regression.•Baseline MEP amplitude, age, muscle, and time of day, predicted iTBS response.•Baseline MEP amplitude and timepoint predicted cTBS response.•Specific recommendations are proposed to reduce TBS variability.