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在帕金森病中使用体内电生理学的DBS计算建模方法的评估

Seyyed Bahram Borgheai¹, Bryan Howell², Faical Isbaine³

¹Department of Neurology, Emory University, Atlanta, GA, USA.

Brain stimulation

|October 29, 2025

概括

计算模型可以指导深度大脑刺激 (DBS) 编程. 驱动力-原生路径模型最准确地预测了帕金森病中皮质下路径的激活.

科学领域:

神经科学是一个神经科学.
生物医学工程生物医学工程
计算机建模计算建模

背景情况:

深度大脑刺激 (DBS) 编程需要耗时的试错调整.
正在开发计算模型以优化DBS参数设置.
计算模型准确性用于预测DBS效应的验证仍然有限.

研究的目的:

建立一个用于验证DBS计算模型准确性的框架.
为了比较各种建模方法的预测准确度.
使用帕金森病 (PD) 患者的体内测量来评估模型性能,这些患者接受了亚thalamic核 (STN) DBS.

主要方法:

对比了六种计算建模变化 (驱动力与激活组织体积,原生与规范成像空间,路径与结构表示).
使用的皮层唤起潜力 (cEPs) 延迟时间<2 ms和2-4 ms.
使用cEP振幅和路径/结构激活之间的R平方量化模型性能.

主要成果:

驱动力-本土路径模型在预测皮质下路径激活方面表现出最高的准确性.
使用规范性大脑空间显著降低了模型预测的准确性.
模型准确性在11名PD患者中进行了比较.

结论:

模型选择应与特定应用的精度要求保持一致.
优化模型参数对于准确预测实验激活措施至关重要.
驱动力-原生路径模型显示了准确的DBS路径激活预测的前景.

关键词:

皮层唤起的潜在潜力皮质脊椎管脊椎管中的皮质脊椎管.驱动力是驱动力的驱动力.超直通路径是一种超直通路径.规范空间是一个规范空间.活化组织的体积.

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