Hybrid spiking models

被引：100

作者：

Izhikevich, Eugene M. ^{[1
]}

机构：

[1] Brain Corp, San Diego, CA 92121 USA

来源：

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2010年 / 368卷 / 1930期

关键词：

computational neuroscience; spiking neuron; neuromorphic hardware; FIRE MODEL; NEURONS;

D O I：

10.1098/rsta.2010.0130

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

I review a class of hybrid models of neurons that combine continuous spike-generation mechanisms and a discontinuous 'after-spike' reset of state variables. Unlike Hodgkin-Huxley-type conductance-based models, the hybrid spiking models have a few parameters derived from the bifurcation theory; instead of matching neuronal electrophysiology, they match neuronal dynamics. I present a method of after-spike resetting suitable for hardware implementation of such models, and a hybrid numerical method for simulations of large-scale biological spiking networks.

引用

页码：5061 / 5070

页数：10

共 9 条

[1]

[Anonymous], 2006, Scholarpedia, DOI DOI 10.4249/SCHOLARPEDIA.1408

[2]

[Anonymous], 2010, Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting

[3] Adaptive exponential integrate-and-fire model as an effective description of neuronal activity [J].