中国物理B ›› 2007, Vol. 16 ›› Issue (8): 2479-2485.doi: 10.1088/1009-1963/16/8/054

• 8000 CROSSDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    下一篇

Dynamics analysis on neural firing patterns by symbolic approach

郜志英, 陆启韶   

  1. School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • 收稿日期:2006-11-29 修回日期:2007-03-01 出版日期:2007-08-20 发布日期:2007-08-20
  • 基金资助:
    Project supported by the National Natural Science of China (Grant No~10432010).

Dynamics analysis on neural firing patterns by symbolic approach

Gao Zhi-Ying(郜志英) and Lu Qi-Shao(陆启韶)   

  1. School of Science, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
  • Received:2006-11-29 Revised:2007-03-01 Online:2007-08-20 Published:2007-08-20
  • Supported by:
    Project supported by the National Natural Science of China (Grant No~10432010).

摘要: Neural firing patterns are investigated by using symbolic dynamics. Bifurcation behaviour of the Hindmarsh--Rose (HR) neuronal model is simulated with the external stimuli gradually decreasing, and various firing activities with different topological structures are orderly numbered. Through constructing first-return maps of interspike intervals, all firing patterns are described and identified by symbolic expressions. On the basis of ordering rules of symbolic sequences, the corresponding relation between parameters and firing patterns is established, which will be helpful for encoding neural information. Moreover, using the operation rule of $\ast$ product, generation mechanisms and intrinsic configurations of periodic patterns can be distinguished in detail. Results show that the symbolic approach is a powerful tool to study neural firing activities. In particular, such a coarse-grained way can be generalized in neural electrophysiological experiments to extract much valuable information from complicated experimental data.

Abstract: Neural firing patterns are investigated by using symbolic dynamics. Bifurcation behaviour of the Hindmarsh--Rose (HR) neuronal model is simulated with the external stimuli gradually decreasing, and various firing activities with different topological structures are orderly numbered. Through constructing first-return maps of interspike intervals, all firing patterns are described and identified by symbolic expressions. On the basis of ordering rules of symbolic sequences, the corresponding relation between parameters and firing patterns is established, which will be helpful for encoding neural information. Moreover, using the operation rule of $\ast$ product, generation mechanisms and intrinsic configurations of periodic patterns can be distinguished in detail. Results show that the symbolic approach is a powerful tool to study neural firing activities. In particular, such a coarse-grained way can be generalized in neural electrophysiological experiments to extract much valuable information from complicated experimental data.

Key words: neural firing patterns, interspike interval, first-return map, symbolic sequence

中图分类号:  (Nonlinear dynamics and chaos)

  • 05.45.-a
07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)