Department of Biomedical Engineering, Duke University, Durham, NC, United States of America.
Department of Neurosurgery, Duke University, Durham, NC, United States of America.
PLoS One. 2023 Nov 27;18(11):e0294512. doi: 10.1371/journal.pone.0294512. eCollection 2023.
Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are commonly used in research analyses, and are beginning to be used in clinical practice. Computational models of DBS LFPs provide tools for investigating the biophysics and neural synchronization that underlie LFP signals. However, technical standards for DBS LFP model parameterization remain to be established. Therefore, the goal of this study was to evaluate the role of the volume conductor (VC) model complexity on simulated LFP signals in the subthalamic nucleus (STN).
We created a detailed human head VC model that explicitly represented the inhomogeneity and anisotropy associated with 12 different tissue structures. This VC model represented our "gold standard" for technical detail and electrical realism. We then incrementally decreased the complexity of the VC model and quantified the impact on the simulated LFP recordings. Identical STN neural source activity was used when comparing the different VC model variants. Results Ignoring tissue anisotropy reduced the simulated LFP amplitude by ~12%, while eliminating soft tissue heterogeneity had a negligible effect on the recordings. Simplification of the VC model to consist of a single homogenous isotropic tissue medium with a conductivity of 0.215 S/m contributed an additional ~3% to the error.
Highly detailed VC models do generate different results than simplified VC models. However, with errors in the range of ~15%, the use of a well-parameterized simple VC model is likely to be acceptable in most contexts for DBS LFP modeling.
深部脑刺激 (DBS) 电极的局部场电位 (LFP) 记录常用于研究分析,并开始用于临床实践。DBS LFP 的计算模型为研究潜在的生物物理和神经同步提供了工具。然而,DBS LFP 模型参数化的技术标准仍有待建立。因此,本研究的目的是评估容积导体 (VC) 模型复杂性对模拟的丘脑底核 (STN) LFP 信号的作用。
我们创建了一个详细的人体头部 VC 模型,明确表示了与 12 种不同组织结构相关的非均质性和各向异性。该 VC 模型代表了我们在技术细节和电气现实方面的“黄金标准”。然后,我们逐步降低 VC 模型的复杂性,并量化了对模拟 LFP 记录的影响。在比较不同 VC 模型变体时,使用相同的 STN 神经源活动。
忽略组织各向异性将模拟的 LFP 幅度降低了约 12%,而消除软组织非均质性对记录几乎没有影响。将 VC 模型简化为具有 0.215 S/m 电导率的单一均质各向同性组织介质会额外增加约 3%的误差。
高度详细的 VC 模型确实会产生与简化 VC 模型不同的结果。然而,由于误差在 15%左右,因此在大多数情况下,使用参数良好的简单 VC 模型进行 DBS LFP 建模可能是可以接受的。