University of Twente Student Theses


In silico modeling of neuronal network dynamics in GEFS+ and Dravet Syndrome.

Doorn, Nina (2021) In silico modeling of neuronal network dynamics in GEFS+ and Dravet Syndrome.

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Abstract:Generalized Epilepsy with Febrile Seizures Plus (GEFS+) and Dravet Syndrome (DS) are two epilepsy syndromes in the same spectrum, with divergent clinical phenotypes, that can both be caused by a mutation in the voltage-gated sodium channel of neurons. The pathophysiological mechanisms underlying GEFS+ and DS are far from understood. In vitro neuronal networks derived from healthy control- and patient stem cells show distinct differences in spontaneous electrical network activity. The processes underlying these differences are challenging to unravel. Here, we use an in silico model to elucidate the role of sodium channel mutations and network dynamics in explaining the in vitro observations. We combine existing models to obtain a model of 100 thermodynamic Hodgkin-Huxley neurons, including spike-frequency adaptation, sparsely connected via plastic AMPA and NMDA synapses. We first calibrate parameters such that the model can replicate the behavior observed from healthy (WT) neuronal networks. For GEFS+ and DS, we modify the voltage-gated sodium channel dynamics. Our model faithfully reproduces the behavior of the WT cultures. We found that changes in sodium channel dynamics were not sufficient to reproduce the behavior of the GEFS+ and DS cultures. Additional downscaling of the synaptic weights and adaptive mechanisms resulted in network behavior similar to that of GEFS+ and DS cultures. Our results suggest that homeostatic synaptic plasticity, modeled by downscaling of the synaptic weights, has a considerable influence on the behavior of GEFS+ and DS neuronal networks.This could potentially explain the large inter-patient variability in clinical phenotypes and tractability. To further validate these hypotheses, the influence of homeostatic plasticity needs to be evaluated in vitro and the computational model needs to be expanded to incorporate long-term plasticities.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine
Programme:Biomedical Engineering MSc (66226)
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