Parameter Estimation for Coupling Neural Network Models with Symbolic Dynamics

摘要：

This paper presents work on parameter estimation method for simple coupling neural network models. Different from the traditional voltage-clamp technique to extract each ion channel parameters of a neuron, the method proposed in this paper only need to record the inter-spike interval sequences of the neurons output. Based on the principle of symbolic dynamics, the action potential sequences can be symbolized without high precision measurement. By computing the distance between symbolic sequences can analyze the degree of nearness between the two orbits, and then use dichotomy to find the optimal parameters. The longer the output spike sequence is, the higher precision estimation can be achieved. The proposed method is efficient for parameter estimation in unstable neural systems, and has a certain reference value for creating neural models from neural electrophysiological experiments.

作者: Jiong Ding Hong Zhang QinYe Tong

作者单位: Biomedical Engineering Department, Zhe Jiang University,China Biomedical Engineering Department, Zhe Jiang University, China

会议类型: 国际会议

会议名称: 2011 International Symposium on Bioelectronics and Bioinformatics(第二届国际生物医学电子学与生物信息学学术会议 ISBB 2011)

会议地点: 苏州

会议语种:英文

页码: 275-278

在线出版日期: 2011-11-03（万方平台首次上网日期，不代表论文的发表时间）