Repeated co-activation of two neurons strengthens the connection between them — the basic mechanism behind all associative learning.
w(t+1) = w(t) + eta * pre * post (Hebbian rule)
fire if potential > threshold
- Neuron count — simulated neurons arranged as a small cortical-style network.
- Synaptic density — how many neurons any given neuron is wired to.
- Learning rate — how strongly a used synapse strengthens each time it fires (Hebbian plasticity).
- Firing threshold — membrane potential a neuron must accumulate before it fires.
This 'fire together, wire together' rule is the same Hebbian principle behind how practice turns a clumsy new skill into an automatic one.