Chaotic balanced state in a model of cortical circuits
Neural Computation
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Characterization of Triphasic Rhythms in Central Pattern Generators (II): Burst Information Analysis
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Effects of different connectivity patterns in a model of cortical circuits
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Simple model of spiking neurons
IEEE Transactions on Neural Networks
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Sets of coupled neurons can generate many different patterns in response to modulatory or sensory inputs. The study of how these patterns have been generated from the inputs has been object of great interest in the literature. These studies have been mainly performed by means of computer simulations, based on differential models or phenomenological models. However complete descriptions of the behaviour of sets of coupled neurons are hard to obtain due to the complex behaviour of the dynamics generated even by the simplest neuron models and for the high number of parameters involved. Here we present a study of a three neuron network that appears in models of Central Pattern Generators. The use of a lineal model allows a complete dynamical description of the system, identifying the relevant situations and drawing some conclusions concerning the dynamics of the network.