Neural Network STDP Simulation

About this simulation:

This simulation models spike-timing dependent plasticity (STDP) in a neural network with excitatory and inhibitory neurons. You can adjust the noise parameter σ (sigma) to see how it affects the synaptic weights W_EE and W_EI over time.

Sigma (σ) - Noise Parameter: Enter a value between 0 and 1 (e.g., 0.1, 0.2, 0.5)

aE - Excitatory Drive: Excitatory neuron drive parameter (typical range: 10-50)

aI - Inhibitory Drive: Inhibitory neuron drive parameter (typical range: 10-50)

Simulation Time (seconds): Total simulation duration in seconds (5-200)

Initial w_EE: Initial excitatory-to-excitatory weight (minimum 0)

Initial w_EI: Initial excitatory-to-inhibitory weight (minimum 0)

Typical parameter combinations to try:

σ = 0.1, aE = 20, w_EE = 10, w_EI = 10, Time = 10s (standard)
σ = 0.3, aE = 30, w_EE = 10, w_EI = 10, Time = 20s (higher activity)
σ = 0.0, aE = 15, w_EE = 10, w_EI = 10, Time = 50s (no noise, longer)
σ = 0.5, aE = 25, w_EE = 10, w_EI = 10, Time = 30s (high noise)