Chaotic solutions in the quadratic integrate-and-fire neuron with adaptation

被引：18

作者：

Zheng, Gang ^{[1
]}

Tonnelier, Arnaud ^{[2
]}

机构：

[1] ENSEA, ECS, F-95014 Cergy Pontoise, France

[2] LJK, INRIA, F-38334 Saint Ismier, France

来源：

COGNITIVE NEURODYNAMICS | 2009年 / 3卷 / 03期

关键词：

QIF; Chaos; Poincare map; Lyapunov exponent; THRESHOLD FATIGUE; SPIKING NEURONS; MODEL; EXCITABILITY; RELIABILITY;

D O I：

10.1007/s11571-008-9069-6

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

The quadratic integrate-and-fire (QIF) model with adaptation is commonly used as an elementary neuronal model that reproduces the main characteristics of real neurons. In this paper, we introduce a QIF neuron with a nonlinear adaptive current. This model reproduces the neuron-computational features of real neurons and is analytically tractable. It is shown that under a constant current input chaotic firing is possible. In contrast to previous study the neuron is not sinusoidally forced. We show that the spike-triggered adaptation is a key parameter to understand how chaos is generated.

引用

页码：197 / 204

页数：8

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