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Authors: Sergey Lobov 1 ; Ksenia Balashova 1 ; Valeri A. Makarov 2 and Victor Kazantsev 1

Affiliations: 1 Lobachevsky State University of Nizhny Novgorod, Russian Federation ; 2 Lobachevsky State University of Nizhny Novgorod and Universidad Complutense de Madrid, Russian Federation

ISBN: 978-989-758-270-7

Keyword(s): Hebbian Plasticity, Learning, Population Spikes, Population Bursts, Cultured Neural Networks, Models of Neural Networks.

Related Ontology Subjects/Areas/Topics: Health Engineering and Technology Applications ; Neurocomputing ; Neurotechnology, Electronics and Informatics

Abstract: Population spike or burst signaling is widely observed both in intact brain and neuronal cultures. Experimental evidence suggests that locally applied electrical stimuli can shape the network architecture and thus the neuronal response. However, there is no clue on how this process can be controlled. In this work we study a realistic model of a culture of cortical-like neurons with spike timing dependent plasticity (STDP). We show that the network dynamics is driven by a competition of spike-conducting pathways, which influences the learning ability of the network. Even in the case of single-electrode stimulation the network dynamics can be complex. Self-establishing spike-conducting pathways, different from those we expect to strengthen, can interfere the process of the network structuring. It leads to an intermittent regime: the time intervals of well-pronounced population spikes synchronized with the stimulus are alternated by intervals of asynchronous dynamics. Under multi-electro de stimulation of an unstructured network the competition of spike-conducting pathways destroys the unconditional learning. The STDP stimulation protocol fails to work at the network scale. To overcome this restriction we propose to use structured neural network and show that one can train such a network and achieve spiking activity circulating in the network after the stimulus has been switched off. (More)

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Paper citation in several formats:
Lobov S., Balashova K., Makarov V. and Kazantsev V. (2017). Competition of Spike-Conducting Pathways in STDP Driven Neural Networks.In Proceedings of the 5th International Congress on Neurotechnology, Electronics and Informatics - NEUROTECHNIX, ISBN 978-989-758-270-7, pages 15-21. DOI: 10.5220/0006497400150021

@conference{neurotechnix17,
author={Sergey Lobov and Ksenia Balashova and Valeri A. Makarov and Victor Kazantsev},
title={Competition of Spike-Conducting Pathways in STDP Driven Neural Networks},
booktitle={Proceedings of the 5th International Congress on Neurotechnology, Electronics and Informatics - NEUROTECHNIX,},
year={2017},
pages={15-21},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006497400150021},
isbn={978-989-758-270-7},
}

TY - CONF

JO - Proceedings of the 5th International Congress on Neurotechnology, Electronics and Informatics - NEUROTECHNIX,
TI - Competition of Spike-Conducting Pathways in STDP Driven Neural Networks
SN - 978-989-758-270-7
AU - Lobov S.
AU - Balashova K.
AU - Makarov V.
AU - Kazantsev V.
PY - 2017
SP - 15
EP - 21
DO - 10.5220/0006497400150021

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