Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus
Currin C, Burman RJ, Fedele T, Ramantani G, Rosch RE, Sprekeler H, Raimondo JV. 2025. Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. Neurobiology of Disease. 212, 106966.
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Journal Article
| Epub ahead of print
| English
Scopus indexed
Author
Currin, ChristopherISTA
;
Burman, Richard J.;
Fedele, Tommaso;
Ramantani, Georgia;
Rosch, Richard E.;
Sprekeler, Henning;
Raimondo, Joseph V.

Department
Abstract
Status epilepticus (SE), seizures lasting beyond five minutes, is a medical emergency commonly treated with benzodiazepines which enhance GABAA receptor (GABAAR) conductance. Despite widespread use, benzodiazepines fail in over one-third of patients, potentially due to seizure-induced disruption of neuronal chloride (Cl−) homeostasis. Understanding these changes at a network level is crucial for improving clinical translation. Here, we address this using a large-scale spiking neural network model incorporating Cl− dynamics, informed by clinical EEG and experimental slice recordings. Our simulations confirm that the GABAAR reversal potential (EGABA) dictates the pro- or anti-seizure effect of GABAAR conductance modulation, with high EGABA rendering benzodiazepines ineffective or excitatory. We show SE-like activity and EGABA depend non-linearly on Cl− extrusion efficacy and GABAAR conductance. Critically, cell-type specific manipulations reveal that pyramidal cell, not interneuron, Cl− extrusion predominantly determines the severity of SE activity and the response to simulated benzodiazepines. Leveraging these mechanistic insights, we develop a predictive framework mapping network states to Cl− extrusion capacity and GABAergic load, yielding a proposed decision-making strategy to guide therapeutic interventions based on initial treatment response. This work identifies pyramidal cell Cl− handling as a key therapeutic target and demonstrates the utility of biophysically detailed network models for optimising SE treatment protocols.
Publishing Year
Date Published
2025-05-20
Journal Title
Neurobiology of Disease
Publisher
Elsevier
Acknowledgement
The research leading to these results has received support from the National Research Foundation of South Africa, the Deutscher Akademischer Austauschdienst, NOMIS Foundation, NVIDIA Academic Program, the University of Cape Town, the Anna Mueller Grocholski Foundation, the Swiss National Science Foundation (SNSF: 208184), the Gabriel Foundation, a Wellcome Trust Seed Award (214042/Z/18/Z), the South African Medical Research Council and the FLAIR Fellowship Programme (FLR\R1\190829): a partnership between the African Academy of Sciences and the Royal Society funded by the UK Government's Global Challenges Research Fund and a Wellcome Trust International Intermediate Fellowship (222968/Z/21/Z).
Volume
212
Article Number
106966
ISSN
eISSN
IST-REx-ID
Cite this
Currin C, Burman RJ, Fedele T, et al. Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. Neurobiology of Disease. 2025;212. doi:10.1016/j.nbd.2025.106966
Currin, C., Burman, R. J., Fedele, T., Ramantani, G., Rosch, R. E., Sprekeler, H., & Raimondo, J. V. (2025). Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. Neurobiology of Disease. Elsevier. https://doi.org/10.1016/j.nbd.2025.106966
Currin, Christopher, Richard J. Burman, Tommaso Fedele, Georgia Ramantani, Richard E. Rosch, Henning Sprekeler, and Joseph V. Raimondo. “Network Models Incorporating Chloride Dynamics Predict Optimal Strategies for Terminating Status Epilepticus.” Neurobiology of Disease. Elsevier, 2025. https://doi.org/10.1016/j.nbd.2025.106966.
C. Currin et al., “Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus,” Neurobiology of Disease, vol. 212. Elsevier, 2025.
Currin C, Burman RJ, Fedele T, Ramantani G, Rosch RE, Sprekeler H, Raimondo JV. 2025. Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus. Neurobiology of Disease. 212, 106966.
Currin, Christopher, et al. “Network Models Incorporating Chloride Dynamics Predict Optimal Strategies for Terminating Status Epilepticus.” Neurobiology of Disease, vol. 212, 106966, Elsevier, 2025, doi:10.1016/j.nbd.2025.106966.
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