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. 2020 Jul 28;11:3771. doi: 10.1038/s41467-020-17343-w

Fig. 3. GRS asymmetrically and dynamically modulates the speed of learning.

Fig. 3

a Posterior density over wR for the FMRI experiment as well as the two behavioral experiments. b Percentage of posterior distribution shown in panel a that is bigger than zero (83% for the fMRI experiment, and 87% and 95% for behavioral experiments 1 and 2, respectively). c Average PEs binned by current outcome (Reward/No reward) and R-trace (low/high; median split) show the offset of PE coding generated by positive wR. d Absolute PEs plotted as in panel c illustrate stronger positive value updates when R-trace is high and stronger negative value updates when R-trace is low (ANOVA interaction effect; asterisk indicates p < 0.001). e Estimated effective learning rates of the model demonstrate that the speed of learning differs based on both the type of current outcome and the GRS (ANOVA interaction effect; asterisk indicates p < 0.001). Note the similarity to panel d. f, g BICint and exceedance probability indicate that the full model fits better than one using either asymmetric (AsyAlpha) or dynamic learning rates (DynAlpha). The dashed red line indicates an exceedance probability of 0.95. (in all panels except, error bars indicate ±SEM around the mean across all experimental sessions with n = 65). Source data are provided as Source Data file. Symbols in panel c indicate monkey identity in panels ce; MK abbreviates monkey.