Large-scale analysis of interindividual variability in theta-burst stimulation data: Results from the ‘Big TMS Data Collaboration’

Daniel T. Corp, Hannah G.K. Bereznicki, Gillian M. Clark, George J. Youssef, Peter J. Fried, Ali Jannati, Charlotte B. Davies, Joyce Gomes-Osman, Julie Stamm, Sung Wook Chung, Steven J. Bowe, Nigel C. Rogasch, Paul B. Fitzgerald, Giacomo Koch, Vincenzo Di Lazzaro, Alvaro Pascual-Leone, Peter G. Enticott, the ‘Big TMS Data Collaboration’

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Background: 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. Objective/Hypothesis: 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. Methods: 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. Results: 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. Conclusions: 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.

Original languageEnglish
Pages (from-to)1476-1488
Number of pages13
JournalBrain Stimulation
Issue number5
Publication statusPublished - 1 Sep 2020


  • Big data
  • Theta-burst stimulation
  • Transcranial, and magnetic stimulation
  • Variability

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