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Authors: Elisabetta De Maria 1 ; Daniel Gaffé 2 ; Cédric Girard Riboulleau 3 and Annie Ressouche 4

Affiliations: 1 Univ. Cote d’Azur, CNRS, I3S, France ; 2 Univ. Cote d’Azur, CNRS, LEAT, France ; 3 Univ. Cote d’Azur, INRIA SAM, France ; 4 INRIA SAM, France

Keyword(s): Neural Spiking Networks, Probabilistic Models, Temporal Logic, Model Checking, Network Reduction.

Abstract: In this paper we formalize Boolean Probabilistic Leaky Integrate and Fire Neural Networks as Discrete-Time Markov Chains using the language PRISM. In our models, the probability for neurons to emit spikes is driven by the difference between their membrane potential and their firing threshold. The potential value of each neuron is computed taking into account both the current input signals and the past potential value. Taking advantage of this modeling, we propose a novel algorithm which aims at reducing the number of neurons and synaptical connections of a given network. The reduction preserves the desired dynamical behavior of the network, which is formalized by means of temporal logic formulas and verified thanks to the PRISM model checker.

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Paper citation in several formats:
De Maria, E.; Gaffé, D.; Girard Riboulleau, C. and Ressouche, A. (2018). A Model-checking Approach to Reduce Spiking Neural Networks. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - BIOINFORMATICS; ISBN 978-989-758-280-6; ISSN 2184-4305, SciTePress, pages 89-96. DOI: 10.5220/0006572000890096

@conference{bioinformatics18,
author={Elisabetta {De Maria}. and Daniel Gaffé. and Cédric {Girard Riboulleau}. and Annie Ressouche.},
title={A Model-checking Approach to Reduce Spiking Neural Networks},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - BIOINFORMATICS},
year={2018},
pages={89-96},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006572000890096},
isbn={978-989-758-280-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - BIOINFORMATICS
TI - A Model-checking Approach to Reduce Spiking Neural Networks
SN - 978-989-758-280-6
IS - 2184-4305
AU - De Maria, E.
AU - Gaffé, D.
AU - Girard Riboulleau, C.
AU - Ressouche, A.
PY - 2018
SP - 89
EP - 96
DO - 10.5220/0006572000890096
PB - SciTePress

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