Fig. 1
From: Increased striatal activity in adolescence benefits learning
Mixed-model analyses for development of striatal subregions. a Feedback-learning task, b predicted trajectories for feedback-learning performance (dotted lines represent 95% confidence intervals), c anatomical ROIs in striatal subregions (dark blue = dorsal caudate, light blue = ventral caudate, red = nucleus accumbens), d predicted trajectories for sensitivity to learning signals (contrast learning > application). A quadratic age effect was the best fit for dorsal caudate (no age: Akaike Information Criterion (AIC) = 2337; linear: AIC = 2339, log-like p = 0.606; quadratic: AIC = 2335, log-like p = 0.020), ventral caudate (no age: AIC = 2370; linear: AIC = 2355, log-like p < 0.001; quadratic: AIC = 2339, log-like p < 0.001) and nucleus accumbens (no age: AIC = 2082; linear: AIC = 2056, log-like p < 0.001; quadratic: AIC = 2050, log-like p = 0.004). e Predicted trajectories for sensitivity to valence (contrast positive > negative learning). The best model for dorsal caudate revealed no age-related changes (no age: AIC = 2744; linear: AIC = 2746, log-like p = 0.662; quadratic: AIC = 2748, log-like p = 0.487), a linear age effect for ventral caudate (no age: AIC = 2826; linear: AIC = 2820, log-like p = 0.007; quadratic: AIC =0.2819, log-like p = 0.082), and a quadratic age effect for nucleus accumbens (no age: AIC = 2536; linear: AIC = 2521, log-like p < 0.001; quadratic: AIC = 2516, log-like p = 0.013) (N = 736 scans)
