Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States.
Department of Neurosurgery, Duke University, Durham, North Carolina, United States.
J Neurophysiol. 2024 Jul 1;132(1):136-146. doi: 10.1152/jn.00287.2023. Epub 2024 Jun 12.
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for Parkinson's disease, but its mechanisms of action remain unclear. Detailed multicompartment computational models of STN neurons are often used to study how DBS electric fields modulate the neurons. However, currently available STN neuron models have some limitations in their biophysical realism. In turn, the goal of this study was to update a detailed rodent STN neuron model originally developed by Gillies and Willshaw in 2006. Our design requirements consisted of explicitly representing an axon connected to the neuron and updating the ion channel distributions based on the experimental literature to match established electrophysiological features of rodent STN neurons. We found that adding an axon to the STN neuron model substantially altered its firing characteristics. We then used a genetic algorithm to optimize biophysical parameters of the model. The updated model exhibited spontaneous firing, action potential shape, hyperpolarization response, and frequency-current curve that aligned well with experimental recordings from STN neurons. Subsequently, we evaluated the general compatibility of the updated biophysics by applying them to 26 different STN neuron morphologies derived from three-dimensional anatomical reconstructions. The different morphologies affected the firing behavior of the model, but the updated biophysics were robustly capable of maintaining the desired electrophysiological features. The new STN neuron model developed in this work offers a valuable tool for studying STN neuron firing properties and may find application in simulating STN local field potentials and analyzing the effects of STN DBS. This study presents an anatomically and biophysically realistic rodent STN neuron model. The work showcases the use of a genetic algorithm to optimize the model parameters. We noted a substantial influence of the axon on the electrophysiological characteristics of STN neurons. The updated model offers a valuable tool to investigate the firing of STN neurons and their modulation by intrinsic and/or extrinsic factors.
深部脑刺激(DBS)丘脑底核(STN)是治疗帕金森病的有效方法,但作用机制仍不清楚。详细的多室 STN 神经元计算模型通常用于研究 DBS 电场如何调节神经元。然而,目前可用的 STN 神经元模型在生物物理真实性方面存在一些局限性。反过来,这项研究的目标是更新 Gillies 和 Willshaw 于 2006 年开发的详细啮齿动物 STN 神经元模型。我们的设计要求包括明确表示与神经元相连的轴突,并根据实验文献更新离子通道分布,以匹配啮齿动物 STN 神经元的已建立电生理特征。我们发现,向 STN 神经元模型添加轴突会极大地改变其放电特性。然后,我们使用遗传算法优化模型的生物物理参数。更新后的模型表现出自发放电、动作电位形状、超极化反应和频率电流曲线,与 STN 神经元的实验记录非常吻合。随后,我们通过将更新后的生物物理学应用于从三维解剖重建中得出的 26 种不同的 STN 神经元形态,评估了更新后的生物物理学的一般兼容性。不同的形态会影响模型的放电行为,但更新后的生物物理学能够稳健地保持所需的电生理特征。这项工作中开发的新 STN 神经元模型为研究 STN 神经元放电特性提供了有价值的工具,并可能在模拟 STN 局部场电位和分析 STN DBS 的影响方面得到应用。本研究提出了一种具有解剖学和生物物理意义的啮齿动物 STN 神经元模型。该研究展示了使用遗传算法优化模型参数。我们注意到轴突对 STN 神经元电生理特征有很大影响。更新后的模型为研究 STN 神经元的放电及其被内在和/或外在因素的调制提供了有价值的工具。
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