Hodgkin-Huxley PINN Project

This project implements a Physics-Informed Neural Network (PINN) to solve the Hodgkin-Huxley model equations for neural action potentials.

Project Structure

• verify_hh.py: Numerical solution using Scipy as a baseline.
• hodgkin_neural_net1.py: PINN implementation using PyTorch, including loss tracking.
• plot_results.py: Comparison between numerical and PINN results.
• show_values_and_plot_3d.py: 3D visualization of gating variables ($V$, $t$, $\alpha$).

Features

• ODE Integration: Solves HH equations numerically.
• PINN Training: Trains a neural network with IC and ODE losses.
• Visualization:
  • Gating variable trajectories.
  • 3D plots showing $V(t, \alpha)$.
  • Training loss history (log scale).

Usage

1. Run the baseline: python verify_hh.py
2. Train the PINN: python hodgkin_neural_net1.py
3. Plot results: python plot_results.py
4. 3D visualization: python show_values_and_plot_3d.py