This repository contains computational models for simulating neuronal activity in epileptic brain tissue, from single-neuron dynamics to population-level behavior. The project was developed as part of the exam of the Brain Modeling course during my Bachelor in Artificial Intelligence.
The project implements two complementary approaches to modeling epileptic seizures:
- Microscale (single neuron): Hodgkin-Huxley model with pathological ion channel dynamics
- Mesoscale (neuronal populations): Wendling neural mass model for local field potentials
*Simulated 30-second epileptic seizure event showing smooth transitions through different neuronal states*
Classic conductance-based model for neuronal action potentials with extensions for seizure-like activity:
- Normal spiking behavior with external current injection
- Pathological activity through time-varying Na⁺ and K⁺ conductances
- Smooth transitions from normal to seizure states using sigmoid functions
Population-level model simulating interactions between pyramidal cells and inhibitory interneurons:
- Three neuronal populations (pyramidal, slow inhibitory, fast inhibitory)
- Six distinct epileptic states from background to full ictal activity
- Realistic local field potential (LFP) generation
The model reproduces six distinct epileptic activity patterns:
| Type | A | B | G | Description |
|---|---|---|---|---|
| 1 | 3.0 | 26 | 10 | Background activity |
| 2 | 4.0 | 26 | 10 | Sporadic spikes |
| 3 | 5.0 | 22 | 10 | Rhythmic spikes |
| 4 | 4.0 | 15 | 22 | Slow quasi-sinusoidal |
| 5 | 6.5 | 10 | 22 | Low voltage rapid activity |
| 6 | 7.0 | 18 | 2 | Fast activity (ictal) |
Parameters:
- A: Excitatory synaptic gain
- B: Slow inhibitory synaptic gain
- G: Fast inhibitory synaptic gain
This work is based on the following papers:
Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology, 117(4), 500-544. DOI: 10.1113/jphysiol.1952.sp004764
Wendling, F., Bartolomei, F., Bellanger, J. J., & Chauvel, P. (2002). Epileptic fast activity can be explained by a model of impaired GABAergic dendritic inhibition. European Journal of Neuroscience, 15(9), 1499-1508. DOI: 10.1046/j.1460-9568.2002.01985.x
- Numerical integration: Runge-Kutta 4th order (RK45)
- Time step: Variable (adaptive)
- Simulation time: 120 ms
- Numerical integration: Euler method
- Sampling frequency: 512 Hz
- Time step: ~1.95 ms
I would like to highlight the importance of the seminal papers by Wendling et al. (2002) and Hodgkin & Huxley (1952), fundamental contributions to computational neuroscience and epilepsy research.
