Table 1. Parameters of the integration and extrema detection models (with flat bounds) fit to mean RT data.

∆BICs are relative to the fit of the integration model. Positive values indicate that integration produced a better fit/prediction.

Model	Integration						Extrema detection
Subject	S1	S2	S3	S4	S5	S6	S1	S2	S3	S4	S5	S6
κ	15.7	13.57	17.53	9.9	21.96	6.69	103.3	55.07	104.87	55.18	130.3	42.64
B	0.87	0.77	0.909	1.25	1.16	0.958	0.0757	0.0727	0.076	0.0786	0.078	0.0766
C0	−0.008	−0.0453	−0.012	−0.006	−0.005	−0.02	−0.006	−0.0448	−0.0121	0.026	0.001	−0.031
${\displaystyle t_{\mathrm{N}\mathrm{D}}}$ mean (empirical)	0.39	0.326	0.394	0.367	0.351	0.42	0.39	0.326	0.394	0.367	0.351	0.42
∆BIC: RT fit	0	0	0	0	0	0	471.36	204.4	202.88	135	494.7	71.74
∆BIC: choice prediction	0	0	0	0	0	0	127.42	90.64	146.38	−31.78	−11.62	121.38