Nguyen Dao T A, Säisänen Laura, Kallioniemi Elisa, Karjalainen Pasi A, Rissanen Saara M, Julkunen Petro
Department of Technical Physics, University of Eastern Finland, Kuopio, Finland.
Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland.
Front Neurosci. 2025 Jan 14;18:1415257. doi: 10.3389/fnins.2024.1415257. eCollection 2024.
Motor evoked potentials (MEPs) are an important measure in transcranial magnetic stimulation (TMS) when assessing neuronal excitability in clinical diagnostics related to motor function, as well as in neuroscience research. However, manual feature extraction from large datasets can be time-consuming and prone to human error, and valuable features, such as MEP polyphasia and duration, are often neglected. Several packages have been developed to simplify the process; however, they are often tailored to specific studies or are not accessible. Here, we introduce MEPFeatX, a verified MATLAB package designed for automated and comprehensive MEP feature extraction across a wide range of stimulation paradigms. MEPFeatX is designed and documented for easy integration into any MEP analysis pipeline. Primed templates for specific paradigms, as well as additional analysis coded in R language, are also provided. Thus, MEPFeatX provides its users with a comprehensive and accurate set of MEP features, along with their visuals, facilitating quick and reliable MEP analysis in TMS studies.
在临床诊断中评估与运动功能相关的神经元兴奋性以及在神经科学研究中，运动诱发电位（MEP）是经颅磁刺激（TMS）中的一项重要测量指标。然而，从大型数据集中手动提取特征可能既耗时又容易出现人为错误，而且诸如MEP多相性和持续时间等有价值的特征常常被忽视。已经开发了几个软件包来简化这一过程；然而，它们通常是针对特定研究量身定制的，或者无法获取。在这里，我们介绍MEPFeatX，这是一个经过验证的MATLAB软件包，旨在跨广泛的刺激范式进行自动化和全面的MEP特征提取。MEPFeatX的设计和文档记录便于轻松集成到任何MEP分析流程中。还提供了特定范式的初始模板以及用R语言编写的额外分析代码。因此，MEPFeatX为用户提供了一套全面且准确的MEP特征及其可视化结果，便于在TMS研究中进行快速可靠的MEP分析。
