TY - JOUR
T1 - Large-scale analysis of interindividual variability in single and paired-pulse TMS data
AU - Corp, Daniel T.
AU - Bereznicki, Hannah G.K.
AU - Clark, Gillian M.
AU - Youssef, George J.
AU - Fried, Peter J.
AU - Jannati, Ali
AU - Davies, Charlotte B.
AU - Gomes-Osman, Joyce
AU - Kirkovski, Melissa
AU - Albein-Urios, Natalia
AU - Fitzgerald, Paul B.
AU - Koch, Giacomo
AU - Di Lazzaro, Vincenzo
AU - Pascual-Leone, Alvaro
AU - Enticott, Peter G.
AU - the ‘Big TMS Data Collaboration’
N1 - Funding Information:
We would like to thank all of the researchers who were kind enough to share the data that they worked so hard to collect. A.J. was supported by postdoctoral fellowships from the Natural Sciences and Engineering Research Council of Canada (NSERC 454617) and the Canadian Institutes of Health Research (CIHR 41791). A.P.-L. was partly supported by the Sidney R. Baer Jr. Foundation, the National Institutes of Health, the National Science Foundation, and DARPA. A.P.-L. serves on the scientific advisory boards for Starlab Neuroscience, Neuroelectrics, Magstim Inc. Nexstim, and Cognito; and is listed as an inventor on several issued and pending patents on the real-time integration of transcranial magnetic stimulation with electroencephalography and magnetic resonance imaging. J.G.O. was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number KL2TR002737. P.B.F. is supported by a NHMRC Practitioner Fellowship (1078567). P.B.F. has received equipment for research from MagVenture A/S, Medtronic Ltd, Neuronetics and Brainsway Ltd. and funding for research from Neuronetics. He is on scientific advisory boards for Bionomics Ltd and LivaNova and is a founder of TMS Clinics Australia. P. G. E. is supported by a Future Fellowship from the Australian Research Council (FT160100077).
Funding Information:
A.J. was supported by postdoctoral fellowships from the Natural Sciences and Engineering Research Council of Canada (NSERC 454617) and the Canadian Institutes of Health Research (CIHR 41791). A.P.-L. was partly supported by the Sidney R. Baer Jr. Foundation, the National Institutes of Health, the National Science Foundation, and DARPA. A.P.-L. serves on the scientific advisory boards for Starlab Neuroscience, Neuroelectrics, Magstim Inc., Nexstim, and Cognito; and is listed as an inventor on several issued and pending patents on the real-time integration of transcranial magnetic stimulation with electroencephalography and magnetic resonance imaging. J.G.O. was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number KL2TR002737. P.B.F. is supported by a NHMRC Practitioner Fellowship (1078567). P.B.F. has received equipment for research from MagVenture A/S, Medtronic Ltd, Neuronetics and Brainsway Ltd. and funding for research from Neuronetics. He is on scientific advisory boards for Bionomics Ltd and LivaNova and is a founder of TMS Clinics Australia. P. G. E. is supported by a Future Fellowship from the Australian Research Council (FT160100077).
Publisher Copyright:
© 2021 International Federation of Clinical Neurophysiology
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/10
Y1 - 2021/10
N2 - 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.
AB - 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.
KW - Big data
KW - Motor threshold
KW - Paired-pulse TMS
KW - Single-pulse TMS
KW - Variability
UR - http://www.scopus.com/inward/record.url?scp=85111561301&partnerID=8YFLogxK
U2 - 10.1016/j.clinph.2021.06.014
DO - 10.1016/j.clinph.2021.06.014
M3 - Article
C2 - 34344609
AN - SCOPUS:85111561301
SN - 1388-2457
VL - 132
SP - 2639
EP - 2653
JO - Clinical Neurophysiology
JF - Clinical Neurophysiology
IS - 10
ER -