Oscillations and irregular emission in networks of linear spiking neurons

The dynamics of a network of randomly connected inhibitory linear integrate and fire (LIF) neurons (with a floor for the depolarization), in the presence of stochastic external afferent input, is considered in various parameter regimes of the neurons and of the network. Applying a technique recently...

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Bibliographic Details
Published in:Journal of computational neuroscience 2001-11, Vol.11 (3), p.249-261
Main Authors: Mongillo, G, Amit, D J
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Animals
Biological Clocks - physiology
Central Nervous System - physiology
firing pattern
Humans
Linear Models
Models, Neurological
Nerve Net - physiology
Neural Inhibition - physiology
Neural Networks (Computer)
Neurons - physiology
Stochastic Processes
Synapses - physiology
Synaptic Transmission - physiology
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Summary:The dynamics of a network of randomly connected inhibitory linear integrate and fire (LIF) neurons (with a floor for the depolarization), in the presence of stochastic external afferent input, is considered in various parameter regimes of the neurons and of the network. Applying a technique recently introduced by Brunel and Hakim, we classify the regimes in which such a network has stable stationary states and in which spike emission rates oscillate. In the vicinity of the bifurcation line, the oscillation frequency and its amplitude are computed and compared with simulations. As for leaky IF neurons, the space of parameters can be compacted into two. Yet despite significant technical differences between the two models, related to both the different dynamics of the depolarization as well as to the different boundary conditions, the qualitative behavior is rather similar. The significance of LIF neurons and of the differences with leaky IF neurons is discussed.
ISSN:0929-5313
1573-6873
DOI:10.1023/A:1013775115140