Reactive model parameter estimates and fit statistics. In the top panel, best fit parameter estimates for boundary height (a), onset delay (tr), execution drift rate (ve), braking drift rate (vb), dynamic bias gain (xb) are listed for each of the candidates reactive stopping models. Additionally, the stop signal onset delay (sso) was estimated for the interactive race model but was not included in the other models. The lower panel contains parameter estimates and fit statistics for the candidate models of contextual modulation between baseline and caution conditions of the reactive task. Parameters that were left free to vary between conditions contain two values, one estimate for the baseline condition and another estimate for the caution condition (see Model fitting for details regarding acquisition of constant parameters and optimization across conditions). In both panels, the last three columns show the χ2 as an absolute index of how well each model fit the data as well as the Akaike information criterion (AIC), and Bayesian information criterion (BIC) as complexity penalized goodness-of-fit measures. Lower values in all three measures imply a better fit to the data.