arXiv 2507.034162025-07-04q-bio.NCcs.SYeess.SYstat.AP

经颅磁刺激诱发运动电位的统计-空间模型及其在闭环程序开发中的应用

Statistical-Spatial Model for Motor Potentials Evoked Through Transcranial Magnetic Stimulation for the Development of Closed-Loop Procedures

Maryam Farahmandrad, Stefan Goetz

备注：: 14 pages, 1 figure

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AI总结：

本文针对TMS闭环方法开发中缺乏真实空间反应模型且实验成本高的问题，提出一个数字孪生式群体模型，可模拟运动诱发电位及个体间/内变异性，支持大规模软件在环测试。

摘要：

初级运动皮层似乎是经颅磁刺激（TMS）的核心区域。它是少数能够提供直接可观测反应的位置之一，其生理特性几乎可作为所有其他TMS靶点的模型或参考，例如通过运动阈值以及相对于其位置的空间靶向来实现。此外，它还为整个大脑设定了安全限值。其易于检测的反应已催生了针对多个方面的闭环方法，例如自动化阈值确定、幅度追踪和靶向。脑刺激方法的高变异性将极大受益于快速、无偏的闭环方法。然而，更有效方法的开发在设计阶段早期就需要合适的模型，以便在无需大量实验的情况下进行调优和测试，因为大量实验耗时且昂贵，甚至在所需规模上根本无法实现。一方面，无法接触实验的理论研究者缺乏真实的脑刺激空间反应模型来开发更好的方法。另一方面，受试者可能不应在未经充分预先测试的情况下暴露于早期闭环方法，因为用于闭环操作所需的尚未充分调优的反馈已知会导致不稳定行为。为弥合这一差距，我们开发了一个数字孪生风格的群体模型，该模型能够生成响应虚拟刺激的运动诱发电位，并包含空间（线圈位置和方向）以及群体中募集情况的统计信息，以表征个体间和个体内的变异性。该模型允许用户模拟不同受试者以及数百万次运行，以用于软件在环测试。该模型包含全部代码，以促进进一步开发。

英文摘要：

The primary motor cortex appears to be in the center of transcranial magnetic stimulation (TMS). It is one of few locations that provide directly observable responses, and its physiology serves as model or reference for almost all other TMS targets, e.g., through the motor threshold and spatial targeting relative to its position. It furthermore sets the safety limits for the entire brain. Its easily detectable responses have led to closed-loop methods for a range of aspects, e.g., for automated thresholding, amplitude tracking, and targeting. The high variability of brain stimulation methods would substantially benefit from fast unbiased closed-loop methods. However, the development of more potent methods would early on in the design phase require proper models that allowed tuning and testing with sufficient without a high number of experiments, which are time-consuming and expensive or even impossible at the needed scale. On the one hand, theoretical researchers without access to experiments miss realistic spatial response models of brain stimulation to develop better methods. On the other hand, subjects should potentially not be exposed to early closed-loop-methods without sufficient prior testing as not yet well tuned feed-back as needed for closed-loop operation is known to erratic behavior. To bridge this gap, we developed a digital-twin-style population model that generates motor evoked potentials in response to virtual stimuli and includes statistical information on spatial (coil position and orientation) as well as recruitment in the population to represent inter- and intra-individual variability. The model allows users to simulate different subjects and millions of runs for software-in-the loop testing. The model includes all code to stimulate further development.

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