Joucla Sébastien, Yvert Blaise
CNRS, Institut des Neurosciences Cognitives et Intégratives d’Aquitaine, UMR 5287, Bordeaux F-33000, France.
J Physiol Paris. 2012 May-Aug;106(3-4):146-58. doi: 10.1016/j.jphysparis.2011.10.003. Epub 2011 Oct 20.
Extracellular electrical stimulation of neural networks has been widely used empirically for decades with individual electrodes. Since recently, microtechnology provides advanced systems with high-density microelectrode arrays (MEAs). Taking the most of these devices for fundamental goals or developing neural prosthesis requires a good knowledge of the mechanisms underlying electrical stimulation. Here, we review modeling approaches used to determine (1) the electric potential field created by a stimulation and (2) the response of an excitable cell to an applied field. Computation of the potential field requires solving the Poisson equation. While this can be performed analytically in simple electrode-neuron configurations, numerical models are required for realistic geometries. In these models, special care must be taken to model the potential drop at the electrode/tissue interface using appropriate boundary conditions. The neural response to the field can then be calculated using compartmentalized cell models, by solving a cable equation, the source term of which (called activating function) is proportional to the second derivative of the extracellular field along the neural arborization. Analytical and numerical solutions to this equation are first presented. Then, we discuss the use of approximated solutions to intuitively predict the neuronal response: Either the "activating function" or the "mirror estimate", depending on the pulse duration and the cell space constant. Finally, we address the design of optimal electrode configurations allowing the selective activation of neurons near each stimulation site. This can be achieved using either multipolar configurations, or the "ground surface" configuration, which can be easily integrated in high-density MEAs. Overall, models highlighting the mechanisms of electrical microstimulation and improving stimulating devices should help understanding the influence of extracellular fields on neural elements and developing optimized neural prostheses for rehabilitation.
几十年来，神经网络的细胞外电刺激已通过单个电极在经验层面上得到广泛应用。近来，微技术提供了配备高密度微电极阵列（MEA）的先进系统。充分利用这些设备实现基础目标或开发神经假体需要深入了解电刺激背后的机制。在此，我们回顾用于确定（1）刺激产生的电势场以及（2）可兴奋细胞对施加电场的响应的建模方法。电势场的计算需要求解泊松方程。虽然在简单的电极 - 神经元配置中可以通过解析方法进行计算，但对于实际几何形状则需要数值模型。在这些模型中，必须特别注意使用适当的边界条件来模拟电极/组织界面处的电势降。然后可以使用 compartmentalized 细胞模型，通过求解电缆方程来计算细胞对电场的响应，该方程的源项（称为激活函数）与沿神经分支的细胞外场的二阶导数成正比。首先给出该方程的解析解和数值解。然后，我们讨论使用近似解直观地预测神经元响应：根据脉冲持续时间和细胞空间常数，要么使用“激活函数”，要么使用“镜像估计”。最后，我们探讨允许在每个刺激部位附近选择性激活神经元的最佳电极配置的设计。这可以通过使用多极配置或“接地表面”配置来实现，后者可以轻松集成到高密度 MEA 中。总体而言，突出电微刺激机制并改进刺激设备的模型应有助于理解细胞外场对神经元件的影响，并开发用于康复的优化神经假体。
