Drift-Diffusion Decision Model

Forty independent evidence accumulators race in parallel toward one of two decision boundaries, each following the drift-diffusion model — the mathematical account of how the brain turns a noisy stream of evidence into a fast, discrete choice. Every racer takes its own noisy path: some run straight for the boundary while others wander and even reverse, exactly as reaction-time data from real perceptual and memory decisions look. Tune the drift rate, boundary separation, noise and starting bias to explore the speed-accuracy tradeoff live, and watch the simulated accuracy converge on the closed-form "gambler's ruin" prediction from the theory.