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Modeling of seizure transitions with ion concentration dynamics

Traditionally it is considered that neuronal synchronization in epilepsy is caused by a chain reaction of synaptic excitation. However, it has been shown that synaptic transmission is not necessary for epileptiform synchronization [1]. In order to investigate the respective roles of synaptic and non-synaptic neuronal coupling in seizure transitions, we developed a computational model of hippocampal network, involving extracellular space, realistic dynamics of Na+, K+ and Cl- ions, the glial uptake and diffusion mechanism. We show that network behavior under synaptic coupling conditions may be quite different from the neurons' activities when specific non-synaptic components are included. In particular, we show that in the extended model, strong discharge of inhibitory interneurons may result in long lasting accumulation of extracellular K+, which sustains depolarization of principal cells and causes their pathological discharges. This effect is not present in a reduced, purely synaptic network. These results confirm the experimental hypothesis that increase of inhibitory interneurons firing may lead to increased firing in the pyramidal cells through accumulation of extracellular potassium [2]. The model also shows that all potassium clearance mechanisms (glial uptake, sodium-potassium pump, potassium diffusion) are critically important to reproduce the experimental findings. This means that computational modeling of seizure activity without ion dynamics may lead to unrealistic results.

References

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Correspondence to Damiano Gentiletti.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Gentiletti, D., De Curtis, M., Gnatkovski, V. et al. Modeling of seizure transitions with ion concentration dynamics. BMC Neurosci 16 (Suppl 1), P242 (2015). https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2202-16-S1-P242

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  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2202-16-S1-P242

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