Daniel T Corp1, Hannah G K Bereznicki2, Gillian M Clark2, George J Youssef3, Peter J Fried4, Ali Jannati5, Charlotte B Davies2, Joyce Gomes-Osman6, Melissa Kirkovski2, Natalia Albein-Urios2, Paul B Fitzgerald7, Giacomo Koch8, Vincenzo Di Lazzaro9, Alvaro Pascual-Leone10, 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. 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. 8. 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. 9. Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico, Rome, Italy. 10. Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, 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
OBJECTIVE: This study brought together over 60 transcranial magnetic stimulation (TMS) researchers to create the largest known sample of individual participant single and paired-pulse TMS data to date, enabling a more comprehensive evaluation of factors driving response variability. METHODS: Authors of previously published studies were contacted and asked to share deidentified individual TMS data. Mixed-effects regression investigated a range of individual and study level variables for their contribution to variability in response to single and paired-pulse TMS data. RESULTS: 687 healthy participant's data were pooled across 35 studies. Target muscle, pulse waveform, neuronavigation use, and TMS machine significantly predicted an individual's single-pulse TMS amplitude. Baseline motor evoked potential amplitude, motor cortex hemisphere, and motor threshold (MT) significantly predicted short-interval intracortical inhibition response. Baseline motor evoked potential amplitude, test stimulus intensity, interstimulus interval, and MT significantly predicted intracortical facilitation response. Age, hemisphere, and TMS machine significantly predicted MT. CONCLUSIONS: This large-scale analysis has identified a number of factors influencing participants' responses to single and paired-pulse TMS. We provide specific recommendations to minimise interindividual variability in single and paired-pulse TMS data. SIGNIFICANCE: This study has used large-scale analyses to give clarity to factors driving variance in TMS data. We hope that this ongoing collaborative approach will increase standardisation of methods and thus the utility of single and paired-pulse TMS.
OBJECTIVE: This study brought together over 60 transcranial magnetic stimulation (TMS) researchers to create the largest known sample of individual participant single and paired-pulse TMS data to date, enabling a more comprehensive evaluation of factors driving response variability. METHODS: Authors of previously published studies were contacted and asked to share deidentified individual TMS data. Mixed-effects regression investigated a range of individual and study level variables for their contribution to variability in response to single and paired-pulse TMS data. RESULTS: 687 healthy participant's data were pooled across 35 studies. Target muscle, pulse waveform, neuronavigation use, and TMS machine significantly predicted an individual's single-pulse TMS amplitude. Baseline motor evoked potential amplitude, motor cortex hemisphere, and motor threshold (MT) significantly predicted short-interval intracortical inhibition response. Baseline motor evoked potential amplitude, test stimulus intensity, interstimulus interval, and MT significantly predicted intracortical facilitation response. Age, hemisphere, and TMS machine significantly predicted MT. CONCLUSIONS: This large-scale analysis has identified a number of factors influencing participants' responses to single and paired-pulse TMS. We provide specific recommendations to minimise interindividual variability in single and paired-pulse TMS data. SIGNIFICANCE: This study has used large-scale analyses to give clarity to factors driving variance in TMS data. We hope that this ongoing collaborative approach will increase standardisation of methods and thus the utility of single and paired-pulse TMS.