Fig. 6: Weber variability and volatility -related dmPFC activations.
From: Neural variability in the medial prefrontal cortex contributes to efficient adaptive behavior
A MRI bold activation cluster correlating with volatility estimates from the third-order volatility inference model at outcome time (dark-green, voxel-wise p < 0.001, cluster-wise FWE-corrected p < 0.05) superimposed on the MNI template sagittal slice centered on the activation peak (MNI coordinates: x,y,z = 6,17,50 mm). Light-blue area: same data as in Fig. 5A. B Volatility-related activations averaged over the dark-green cluster shown in (A) at outcome and choice time (leave-one-out procedure removing selection biases). Mean and s.e.m across the n = 22 participants (**p = 0.0023; two-sided one-sample T-tests). C Full variance analyses over the dark-green activation cluster shown in (A), comprising volatility estimates and Weber variability \({\epsilon }_{t}^{{fit}}\) as regressor of interest and factoring out variables of no interest, including RTs, response switches, and RL variables. Error bars are s.e.m. across participants (n = 22). **p = 0.006, ***p = 0.0004, otherwise ps > 0.47; two-sided one-sample T-tests, d.f. =21). D Bayesian model comparison over the n = 22 participants between volatility estimates and Weber variability \({\epsilon }_{t}^{{fit}}\) as concurrent models of both outcome- and choice-related activations in the dark-green cluster shown in (A). Bars are model posterior probabilities. Error bars are Bayesian estimates of s.d. of the model posterior probability. Model exceedance probability Pexc is indicated. All data points show individual subjects’ data. Source data are provided as a Source Data file.
