| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # Parameters | |
| tau_m = 20 # Membrane time constant (ms) | |
| R_m = 1 # Membrane resistance (MΩ) | |
| V_rest = -65 # Resting membrane potential (mV) | |
| V_th = -50 # Spike threshold (mV) | |
| V_reset = -65 # Reset potential (mV) | |
| I = 1.5 # Input current (nA) | |
| dt = 0.1 # Time step (ms) | |
| t = np.arange(0, 100, dt) # Time vector | |
| # Initialize membrane potential | |
| V_m = np.zeros(len(t)) | |
| V_m[0] = V_rest | |
| # Simulate the neuron | |
| for i in range(1, len(t)): | |
| dV = (-(V_m[i-1] - V_rest) + R_m * I) / tau_m | |
| V_m[i] = V_m[i-1] + dV * dt | |
| # Check for spike | |
| if V_m[i] >= V_th: | |
| V_m[i] = 20 # Spike to 20 mV | |
| V_m[i+1] = V_reset # Reset potential | |
| # Plot the results | |
| plt.plot(t, V_m) | |
| plt.title('.159 Neuron Simulation') | |
| plt.xlabel('Time (ms)') | |
| plt.ylabel('Membrane Potential (mV)') | |
| plt.show() |