Brette Romain, Piwkowska Zuzanna, Monier Cyril, Rudolph-Lilith Michelle, Fournier Julien, Levy Manuel, Frégnac Yves, Bal Thierry, Destexhe Alain
Unité de Neurosciences Intégratives et Computationnelles (UNIC), CNRS, 91198 Gif-sur-Yvette, France.
Neuron. 2008 Aug 14;59(3):379-91. doi: 10.1016/j.neuron.2008.06.021.
Intracellular recordings of neuronal membrane potential are a central tool in neurophysiology. In many situations, especially in vivo, the traditional limitation of such recordings is the high electrode resistance and capacitance, which may cause significant measurement errors during current injection. We introduce a computer-aided technique, Active Electrode Compensation (AEC), based on a digital model of the electrode interfaced in real time with the electrophysiological setup. The characteristics of this model are first estimated using white noise current injection. The electrode and membrane contribution are digitally separated, and the recording is then made by online subtraction of the electrode contribution. Tests performed in vitro and in vivo demonstrate that AEC enables high-frequency recordings in demanding conditions, such as injection of conductance noise in dynamic-clamp mode, not feasible with a single high-resistance electrode until now. AEC should be particularly useful to characterize fast neuronal phenomena intracellularly in vivo.
神经元膜电位的细胞内记录是神经生理学中的核心工具。在许多情况下,尤其是在体内,此类记录的传统局限性在于电极的高电阻和电容,这可能在电流注入期间导致显著的测量误差。我们引入了一种基于电极数字模型的计算机辅助技术——有源电极补偿(AEC),该模型与电生理装置实时连接。首先通过注入白噪声电流来估计该模型的特性。电极和膜的贡献在数字上被分离,然后通过在线减去电极贡献来进行记录。在体外和体内进行的测试表明,AEC能够在苛刻条件下进行高频记录,例如在动态钳制模式下注入电导噪声,而这在目前使用单个高电阻电极是不可行的。AEC对于在体内细胞内表征快速神经元现象应该特别有用。