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Author: Mikhail Kiselev

Affiliation: Chuvash State University, Russian Federation

Keyword(s): spiking neural network, dynamic threshold, short term synaptic depression, multiple adaptive regression splines

Abstract: We consider a model of leaky integrate-and-fire neuron with dynamic threshold and a very simple realization of short term synaptic depression mechanism. Model simplicity makes possible creation of very large networks on its basis. Required general properties of these networks can be obtained due to the appropriate selection of neuron parameters. Knowledge of the dependence of neuron firing frequency on presynaptic activity for various neuron parameters is crucial for this selection. Since this dependence cannot be obtained in an exact analytical form we describe the process of building its empirical approximation using the multiple adaptive regression splines algorithm. This methodology can be used for other neuron models.

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Paper citation in several formats:
Kiselev, M. (2014). Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression. In Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2014) - ANNIIP; ISBN 978-989-758-041-3, SciTePress, pages 11-18. DOI: 10.5220/0005119700110018

@conference{anniip14,
author={Mikhail Kiselev.},
title={Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression},
booktitle={Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2014) - ANNIIP},
year={2014},
pages={11-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005119700110018},
isbn={978-989-758-041-3},
}

TY - CONF

JO - Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing (ICINCO 2014) - ANNIIP
TI - Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression
SN - 978-989-758-041-3
AU - Kiselev, M.
PY - 2014
SP - 11
EP - 18
DO - 10.5220/0005119700110018
PB - SciTePress