REDUCTION OF CONDUCTANCE-BASED NEURON MODELS

被引：98

作者：

KEPLER, TB

ABBOTT, LF

MARDER, E

机构：

[1] BRANDEIS UNIV,DEPT PHYS,WALTHAM,MA 02254

[2] BRANDEIS UNIV,DEPT BIOL,WALTHAM,MA 02254

[3] BRANDEIS UNIV,CTR COMPLEX SYST,WALTHAM,MA 02254

来源：

BIOLOGICAL CYBERNETICS | 1992年 / 66卷 / 05期

关键词：

D O I：

10.1007/BF00197717

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a scheme for systematically reducing the number of differential equations required for biophysically realistic neuron models. The techniques are general, are designed to be applicable to a large set of such models and retain in the reduced system as high a degree of fidelity to the original system as possible. As examples, we provide reductions of the Hodgkin-Huxley system and the A-current model of Connor et al. (1977).

引用

页码：381 / 387

页数：7

共 14 条

[1]

ABBOTT LF, 1990, STATISTICAL MECHANIC

[2]

BUCHHOLTZ F, IN PRESS J NEUROPHYS

[3] NEURAL REPETITIVE FIRING - MODIFICATIONS OF HODGKIN-HUXLEY AXON SUGGESTED BY EXPERIMENTAL RESULTS FROM CRUSTACEAN AXONS [J].