This repository hosts the interactive Single-Page Application (SPA) companion to the peer-reviewed research paper, "Unraveling the Network Dynamics of Neural Epilepsy: A Systems-Level Perspective." Historically viewed merely as a localized cellular anomaly, epilepsy is now definitively understood as a disorder of large-scale neural network dynamics. This interactive digital publication translates complex neurobiological mechanisms, epidemiological data, and therapeutic innovations into a highly accessible, dynamic web format.
- Epidemiological Dashboards: Dynamic visualizations of the global treatment gap and drug resistance spectrum using
Chart.js. - Network State Simulator: An interactive tool demonstrating the delicate Excitation/Inhibition (E/I) equilibrium at the synaptic level. Users can toggle between normal physiological homeostasis and a simulated ictal event (seizure) to observe real-time biochemical shifts (Glutamate vs. GABA).
- Therapeutic Efficacy Timeline: An interactive chronological chart tracking the evolution of interventions from 1st-generation pharmacology to projected closed-loop neuromodulation and AI predictive algorithms by 2030.
This project is built to be lightweight, universally accessible, and free of complex build steps.
- Structure: HTML5
- Styling: Tailwind CSS (loaded via CDN)
- Data Visualization: Chart.js (loaded via CDN)
- Logic: Vanilla JavaScript (ES6+)
Because this project is a standalone SPA utilizing CDNs, there are no dependencies to install or build steps to run.
- Run the application: Simply open the Neural Epilepsy file in any modern web browser (Chrome, Firefox, Safari, Edge).
The research presented in this interactive format underscores a critical paradigm shift in epileptology. The management of epilepsy is moving irreversibly from an empirical, symptom-oriented "seizure suppression" model toward a systems-biology approach focused on "neural network restoration."
While the global burden and the persistent ~30% rate of drug-resistant epilepsy remain significant challenges, the integration of high-density connectomic modeling (such as The Virtual Brain) and precision neuromodulation offers a clear path forward. The future of neural epilepsy treatment lies not in broad-spectrum systemic depressants, but in bioelectronic closed-loop systems and predictive multimodal AI. By identifying and correcting hyper-synchronous network states in real-time, we move closer to a future where seizures are prevented before clinical manifestation.
If you use this interactive paper or its underlying concepts in your own research, please cite it as follows:
SAMUELSON G. (2026). Unraveling the Network Dynamics of Neural Epilepsy: A Systems-Level Perspective. Interactive Digital Publication. Neural Epilepsy
This project is licensed under the MIT License - see the LICENSE file for details. This allows for free use, modification, and distribution for both academic and commercial purposes.
Developed and Researched by SAMUELSON G.