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.
Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
Clin Neurophysiol. 2021 Oct;132(10):2639-2653. doi: 10.1016/j.clinph.2021.06.014. Epub 2021 Jul 6.
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.
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.
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.
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.
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.
本研究汇集了超过 60 名经颅磁刺激(TMS)研究人员,创建了迄今为止已知的最大个体参与者单脉冲和双脉冲 TMS 数据样本,从而能够更全面地评估影响反应变异性的因素。
联系了之前发表研究的作者,并要求他们分享匿名的个体 TMS 数据。混合效应回归分析了一系列个体和研究水平变量,以探讨它们对单脉冲和双脉冲 TMS 数据反应变异性的贡献。
共有 35 项研究的 687 名健康参与者的数据被汇总。目标肌肉、脉冲波形、神经导航使用和 TMS 机器显著预测了个体单脉冲 TMS 振幅。基线运动诱发电位振幅、运动皮层半球和运动阈值(MT)显著预测了短间隔皮质内抑制反应。基线运动诱发电位振幅、测试刺激强度、刺激间隔和 MT 显著预测了皮质内易化反应。年龄、半球和 TMS 机器显著预测了 MT。
这项大规模分析确定了影响参与者对单脉冲和双脉冲 TMS 反应的多个因素。我们提供了具体建议,以最大限度地减少单脉冲和双脉冲 TMS 数据中的个体间变异性。
本研究使用大规模分析阐明了驱动 TMS 数据变异性的因素。我们希望这种持续的合作方法将提高方法的标准化程度,从而提高单脉冲和双脉冲 TMS 的实用性。