Simple central pattern generator model using phasic analog neurons

被引:7
作者
McMillen, DR
D'Eleuterio, GMT
Halperin, JRP
机构
[1] Univ Toronto, Inst Aerosp Studies, Toronto, ON M3H 5T6, Canada
[2] Univ Toronto, Dept Zool, Toronto, ON M5S 3G5, Canada
来源
PHYSICAL REVIEW E | 1999年 / 59卷 / 06期
关键词
D O I
10.1103/PhysRevE.59.6994
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
Many biological neurons (called phasic or adapting neurons) display neural adaptation: their response to a constant input diminishes with time. A simple method of adding adaptive firing thresholds to existing analog (or graded-response) neural models is described. A half-center central pattern generator is modeled using two mutually inhibitory phasic analog neurons. Hopf bifurcation analysis shows that oscillatory solutions will arise if the mutual inhibition is sufficiently strong, and allows us to characterize the stability of the cycles which arise.
引用
收藏
页码:6994 / 6999
页数:6
相关论文
共 37 条
[1]  
[Anonymous], 1988, INTRO THEORETICAL NE
[2]  
[Anonymous], PRINCIPLES NEURAL SC
[3]  
Atiya A., 1989, International Journal of Neural Systems, V1, P103, DOI 10.1142/S0129065789000025
[4]  
ATWOOD HL, 1995, AM ZOOL, V35, P28
[5]  
Beer Randall D., 1992, Adaptive Behavior, V1, P91, DOI 10.1177/105971239200100105
[6]   Desynchronization, mode locking, and bursting in strongly coupled integrate-and-fire oscillators [J].
Bressloff, PC ;
Coombes, S .
PHYSICAL REVIEW LETTERS, 1998, 81 (10) :2168-2171
[8]   ABSOLUTE STABILITY OF GLOBAL PATTERN-FORMATION AND PARALLEL MEMORY STORAGE BY COMPETITIVE NEURAL NETWORKS [J].
COHEN, MA ;
GROSSBERG, S .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1983, 13 (05) :815-826
[9]   HEXAPODAL GAITS AND COUPLED NONLINEAR OSCILLATOR MODELS [J].
COLLINS, JJ ;
STEWART, I .
BIOLOGICAL CYBERNETICS, 1993, 68 (04) :287-298
[10]   A class of convergent neural network dynamics [J].
Fiedler, B ;
Gedeon, T .
PHYSICA D, 1998, 111 (1-4) :288-294