Che Yan-Qiu, Wang Jiang, Li Hui-Yan, Wei Xi-Le, Deng Bing, Dong Feng
School of Electrical Engineering and Automation, Tianjin University, Tianjin, P. R. China.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3433-6. doi: 10.1109/IEMBS.2009.5332510.
As an important neuron model, the Morris-Lecar (ML) equations can exhibit classes I and II excitabilities with appropriate system parameters. In this paper, the effects of external DC electric field on the neuro-computational properties of ML model are investigated using bifurcation analysis. We obtain the bifurcation diagram in two dimensional parameter space of externally applied DC current and trans-membrane potential induced by external DC electric field. The bifurcation sets partition the two dimensional parameter space about the qualitatively different behaviors of the ML model. Thus the neuron's information encodes the stimulus information, and vice versa, which is significant in neural control. Furthermore, we identify the electric field as a key parameter to control the transitions among four different excitability and spiking properties.
作为一种重要的神经元模型，莫里斯 - 莱卡（ML）方程在适当的系统参数下可呈现I类和II类兴奋性。本文利用分岔分析研究了外部直流电场对ML模型神经计算特性的影响。我们在外部施加的直流电流和外部直流电场诱导的跨膜电位的二维参数空间中获得了分岔图。分岔集根据ML模型的定性不同行为划分二维参数空间。因此，神经元的信息编码刺激信息，反之亦然，这在神经控制中具有重要意义。此外，我们确定电场是控制四种不同兴奋性和放电特性之间转变的关键参数。
