CNS*2026 Halifax

Hannah van Susteren^1,*, Guillaume Girier^2,*, Michel J.A.M. van Putten^3,4 , Jaroslav Hlinka², Helmut Schmidt², Hil G.E. Meijer¹


1 Department of Applied Mathematics, University of Twente, Enschede, the Netherlands
2 Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
3 Department of Neurology and Clinical Neurophysiology, University of Twente, Enschede, the Netherlands
4 Medisch Spectrum Twente, Enschede, the Netherlands
* These authors contributed equally to this work.


Email: [email protected]


Introduction
Epilepsy is among the most prevalent neurological disorders. The astrocytic excitatory amino acid transporter (EAAT2) plays a key role in regulating excitability, by controlling extracellular glutamate levels and glutamate receptor activation [1,2]. Reduced EAAT2 expression has been reported in several epilepsy patients [1,3]. However, the impact of neuron-astrocyte interactions on hyperexcitability on single cell level is underexplored. We developed a biophysical model of a presynaptic neuron and astrocyte to explore the relation between astrocytic EAAT2-mediated glutamate clearance, presynaptic glutamate receptors and bursting activity.

Methods
We build on our previous work [4,5], where we consider a presynaptic neuron and an astrocyte in a finite extracellular space (ECS). This model describes sodium, potassium, chloride dynamics as well as calcium-dependent exocytosis and glutamate-glutamine (GG) recycling. For this study, we add a potassium bath with diffusion to the ECS to induce neuronal bursting (Fig. 1A). Additionally, we implement the presynaptic glutamate receptors AMPA and NMDA, which are important in regulating hyperexcitability. Lastly, we study the impact of the antiseizure drugs perampanel and memantine by simulating the effect of these AMPA and NMDA receptor antagonists.

Results
We induce neuronal bursting by increasing extracellular potassium in the bath. We first examine how AMPA and NMDA permeabilities affect burst frequency (Fig. 1C), where frequency refers to spike frequency during the last burst or during tonic firing, to fit the NMDA/AMPA ratio to experimental data [6]. Higher permeabilities increase neuronal firing and intracellular calcium, triggering a feedback loop that enhances neuronal glutamate release. Reducing EAAT permeability raises burst frequency and induces tonic firing (Fig. 1B). Finally, AMPA and NMDA antagonists, perampanel and memantine [7], reduce firing despite elevated extracellular glutamate, with perampanel showing a more significant reduction in firing frequency (Fig. 1D). 

Discussion
Our results show that reduced EAAT expression, as observed in several epilepsy patients, results in increased extracellular glutamate and overstimulation of excitatory glutamate receptors. Furthermore, we show that the AMPA and NMDA receptor permeabilities affect burst frequency. Receptor antagonists such as perampanel and memantine are able to reduce firing. In conclusion, our detailed neuron–astrocyte model provides insight into the effects of reduced EAAT expression and receptor antagonists on hyperexcitability.

Figure 1. A: Three-compartment model illustrating the GG-cycle during EAAT2 knockout. B: The membrane potential, spike frequency f and ECS glutamate at different EAAT2 permeabilities. C: Spike frequency within bursts as a function of NMDA and AMPA receptor permeability.  D: Neuronal activity at fixed EAAT2 permeability (PEAAT=0.15 * 103  µm3/ms) under antagonist conditions.

References
[1] Green, J. L., dos Santos, W. F., & Fontana, A. C. K. (2021). Biochemical Pharmacology, 10.1016/j.bcp.2021.114786
[2] Scimemi, A., Tian, H., & Diamond, J. S. (2009). The Journal of Neuroscience, 10.1523/JNEUROSCI.4845-09.2009
[3] Barker-Haliski, M., & White, H. (2015). Cold Spring Harbor perspectives in medicine, 10.1101/cshperspect.a022863
[4] van Susteren, H., Rose, C. R., van Putten, M. J., & Meijer, H. G. (2025). bioRxiv, 10.1101/2025.11.10.687543
[5] Kalia, M., et al. (2021).  PLOS Computational Biology, 10.1371/journal.pcbi.1009019
[6] Watt, A. J., Sjöström, P. J., Häusser, M., Nelson, S. B., & Turrigiano, G. G. (2004).  Nature neuroscience, 10.1038/nn1220
[7] Chen, T.-S., Huang, T.-H., Lai, M.-C., & Huang, C.-W. (2023).  Biomedicines, 10.3390/biomedicines11030783

Acknowledgments
HVS, HGEM, MJAMVP funded from the DFG, FOR2795 ‘Synapses under stress’ to CRR (Prof. Dr. Christine R. Rose) (Ro2327/13-2 and 14-2).
GG, HS, and JH were supported by the ERDF-Project Brain dynamics, No. CZ.02.01.01/00/22\_008/0004643, a Lumina-Quaeruntur fellowship (LQ100302301), and the long-term strategic development financing of the Institute of Computer Science (RVO:67985807).