Extended Data Fig. 2: AIC and BIC scores for the two, three and four parameter logistic function fits.

(Associated with Fig. 2 of the main text) a, AIC scores for each pre- and post-injection and recovery sessions for all muscimol and saline injections (n = 87 sessions) for two, three, and four parameter logistic fits to the performance data. The circles show the AIC score of the logistic fit to each individual session from the n = 87 total sessions (pre-, post- and recovery * 29 injections), and the black, horizontal bars show the mean AIC score. The dotted lines connect the same data sessions that were fit across the two, three, and four parameter fits to see if there were any changes in AIC score between the fits with different number of parameters. The two-parameter logistic model has two parameters: α (decision bias) and β (sensitivity) following the equation p(IF) = 1/(1 + exp(-β (k-α))) (Eq 1 in Methods), which was used to fit the psychometric functions in Fig. 2 and Extended Data MEP_L_fig4Fig. 4. The three parameter logistic model includes: α, β, and ʎ (lapse rate or the difference between perfect performance and the top and bottom asymptotes) following the equation p(IF) = ʎ + (1-2ʎ)/(1 + exp(-β (k-α))). The four parameter logistic model includes: α, β and ʎ (lapse rate or the difference in perfect performance and asymptotic performance for toIF decisions) and γ (lapse rate or the difference in perfect performance and asymptotic performance for awayIF decisions) following the equation p(IF) = γ + (1-γ-λ)/(1 + exp(-β (k-α))). When looking at the AIC scores for the two, three, and four parameter fits (lower AIC scores indicate a better fit given model complexity), we see that the data are explained equally well or better with the models without lapse rates, with mean scores of 638.80 for the two-parameter fit, 640.51 for the three parameter fit, and 641.47 for the four parameter fit. Therefore, we selected the simpler, two-parameter model to fit the performance data. b, Same as in a for the BIC scores, with mean of 639.93 for the two-parameter fit, 642.20 for the three parameter fit, and 643.73 for the four parameter fit. The lack of difference in the quality of the fits with or without the lapse rate parameters is consistent with the parameter estimation results of lapse rates in the hierarchical DDM (Extended Data Fig. 6i,j).