Figure 2.

Bayesian model prediction and behavioral data. A, Bayes-optimal decision-making in the stop-signal task predicts a positive linear relationship between go RT and P(stop) (red squares and line fit). Subjects' go RT positively and linearly correlates with the model estimate of P(stop) on each trial, confirming the prediction. Black circles, mean go RT averaged across subjects for each small bin of P(stop) values; error bars indicate SEM (n = 66); line is best linear regression fit to mean go RT (R² = 0.83, p < 10⁻¹⁵). Histogram, Empirical distribution of model-estimated P(stop). B, Model predicts a decrease in the SE rate as P(stop) increases, as shown by red squares and line fit. Behavioral data, shown in black, also demonstrate a negative linear relationship between SE rate and model-estimated P(stop). Black circles, error bars, and histogram as in A. Black line is best linear regression fit to SE rate (R² = 0.88, p < 10⁻⁵).