Computational modeling of resistance to hormone-mediated remission in childhood absence epilepsy

Childhood absence epilepsy (CAE) often resolves during adolescence, a period marked by hormonal and neurosteroid changes associated with puberty. However, remission does not occur in all individuals. To investigate this clinical heterogeneity, we developed a simplified thalamocortical model with a layered cortical structure, using deep-layer intrinsically bursting (IB) neurons to represent frontal cortex and regular spiking (RS) neurons modeling the parietal cortex. By simulating two cortical configurations, we explored how variations in neuronal composition and frontocortical connectivity influence seizure dynamics and the effectiveness of allopregnanolone (ALLO) in resolving pathological spike-wave discharges (SWDs) associated with CAE. While both models exhibited similar physiological and pathological oscillations, only the parietal-dominant network (with a higher proportion of RS neurons in layer 5) recovered from SWDs under increased frontocortical connectivity following ALLO administration. These findings suggest that neuronal composition critically modulates ALLO-mediated resolution of SWDs, providing a mechanistic link between structural connectivity and clinical outcomes in CAE, and highlighting the potential for personalized treatment strategies based on underlying network architecture.

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Publication Details

Journal
Frontiers in Computational Neuroscience
Published
2026-01-12
DOI
https://doi.org/10.3389/fncom.2025.1733650
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Computational modeling of resistance to hormone-mediated remission in childhood absence epilepsy

Maliha Ahmed, Sue Ann Campbell
Frontiers in Computational Neuroscience
Functional Brain Connectivity Studies
article

Computational modeling of resistance to hormone-mediated remission in childhood absence epilepsy

Maliha Ahmed, Sue Ann Campbell
article en

Abstract

Childhood absence epilepsy (CAE) often resolves during adolescence, a period marked by hormonal and neurosteroid changes associated with puberty. However, remission does not occur in all individuals. To investigate this clinical heterogeneity, we developed a simplified thalamocortical model with a layered cortical structure, using deep-layer intrinsically bursting (IB) neurons to represent frontal cortex and regular spiking (RS) neurons modeling the parietal cortex. By simulating two cortical configurations, we explored how variations in neuronal composition and frontocortical connectivity influence seizure dynamics and the effectiveness of allopregnanolone (ALLO) in resolving pathological spike-wave discharges (SWDs) associated with CAE. While both models exhibited similar physiological and pathological oscillations, only the parietal-dominant network (with a higher proportion of RS neurons in layer 5) recovered from SWDs under increased frontocortical connectivity following ALLO administration. These findings suggest that neuronal composition critically modulates ALLO-mediated resolution of SWDs, providing a mechanistic link between structural connectivity and clinical outcomes in CAE, and highlighting the potential for personalized treatment strategies based on underlying network architecture.

Frontiers in Computational NeuroscienceVol. 19
University of Waterloo (CA), Massachusetts Institute of Technology (US)
University of Waterloo, Natural Sciences and Engineering Research Council of Canada
Good health and well-being
Openalex Percentile: Top 91%
Functional Brain Connectivity Studies
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Computational modeling of resistance to hormone-mediated remission in childhood absence epilepsy — Maliha Ahmed, Sue Ann Campbell · Frontiers in Computational Neuroscience (2026) | TGRS Research Map | TGRS