Fig. 3: Computational parameters and model-free metrics of behavior.
From: Computational mechanisms underlying multi-step planning deficits in methamphetamine use disorder
a Raincloud plots showing distributions for each model parameter by group and resistance condition as well as individual data points connected by thin lines and group means and standard errors depicted by thick lines and confidence ribbons (iMUDs: n = 40; HCs: n = 49). Independent of resistance level, iMUDs had larger AP estimates (F(1,100) = 16.46, p < 0.001, \({\eta }_{p}^{2}=0.14\)) and larger LL-discounting estimates (F(1,100) = 13.45, p < 0.001, \({\eta }_{p}^{2}=0.12\)) than HCs. b Means and standard errors for choice accuracy, which differed by group in trials where the optimal path included large losses (OLL trials; F(1,490) = 25.30, p < 0.001, \({\eta }_{p}^{2}=0.05\)). This was driven by differences at depths 3 and 4. Stars indicate significant effects. LL large loss, NLL no large loss. *p < 0.05, **p < 0.01, ***p < 0.001.
