Daniel T Corp1, Hannah G K Bereznicki2, Gillian M Clark2, George J Youssef3, Peter J Fried4, Ali Jannati5, Charlotte B Davies2, Joyce Gomes-Osman6, Julie Stamm7, Sung Wook Chung8, Steven J Bowe9, Nigel C Rogasch10, Paul B Fitzgerald11, Giacomo Koch12, Vincenzo Di Lazzaro13, Alvaro Pascual-Leone14, Peter G Enticott2. 1. Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. Electronic address: daniel.corp@deakin.edu.au. 2. Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia. 3. Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Australia. 4. Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. 5. Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Neuromodulation Program and Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. 6. Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Department of Physical Therapy, University of Miami Miller School of Medicine, Miami, FL, USA. 7. Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, USA. 8. Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia. 9. Deakin Biostatistics Unit Faculty of Health Deakin University, Geelong, Australia. 10. Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, Australia; Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, Australia; The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia. 11. Monash Alfred Psychiatry Research Centre, Central Clinical School, The Alfred and Monash University, Melbourne, Australia; Epworth Centre for Innovation in Mental Health, Epworth HealthCare and Central Clinical School, Melbourne, Australia. 12. Non-invasive Brain Stimulation Unit, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy; Department of Biomedical and Specialty Surgical Sciences, Section of Human Physiology, University of Ferrara, Italy. 13. Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico, Rome, Italy. 14. Hinda and Arthur Marcus Institute for Aging Research. Hebrew SeniorLife, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Guttmann Brain Health Institute, Institut Guttmann de Neurorehabilitació, Universitat Autonoma de Barcelona, Barcelona, Spain.
Abstract
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.
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 participantTBS 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.
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