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 = 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 stop error (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 panel (A). Black line is best linear regression fit to SE rate (R²=0.88, p<10⁻⁵).