Fig. 5: Neural fluctuations associated with Weber variability.
From: Neural variability in the medial prefrontal cortex contributes to efficient adaptive behavior
A MRI bold activation cluster in the dmPFC associated with Weber variability \({\epsilon \, }_{t}^{{fit}}=\left({\mu }_{{fit}}+{\lambda }_{{fit}}{d}_{t}\right).{U}_{{fit}}^{t}\) at choice time (light-blue, voxel-wise p < 0.001, cluster-wise FWE-corrected p < 0.05), superimposed on the MNI template sagittal slice centered on the voxel exhibiting the maximal correlation. B Weber-variability -related activations averaged over the activation cluster shown in (A) at outcome and choice time (mean ± s.e.m. over the n = 22 participants from a leave-one-out procedure removing selection biases). Note the expected marginal correlation at outcome time (\({{{\boldsymbol{ \sim }}}}\) p = 0.059; ****p < 0.0000001; two-sided one-sample T-tests). C Bayesian model comparison over the n = 22 participants between Weber variability \({\epsilon \, }_{t}^{{fit}}\) and its sole deterministic component \({\mu }_{{fit}}+{\lambda }_{{fit}}{d}_{t}\) as concurrent models of these activations at both outcome and choice time. Bars are model posterior probabilities; error bars are Bayesian estimates of model posterior probability standard deviations. Model exceedance probability Pexc is shown. To remove selection biases, the Bayesian model comparison was performed only on voxels correlating with both \({\epsilon }_{t}^{{fit}}\) and \({\mu }_{{fit}}+{\lambda }_{{fit}}{d}_{t}\) (voxel-wise threshold p < 0.001) and through a leave-one-out procedure. D, left: model with \({U}_{{fit}}^{t}\) as the unique regressor (**p = 0.0045; ****p = 0.0000051; one-sample two-sided T-tests, d.f. = 21); right: full variance analyses over these voxels comprising Weber variability \({\epsilon \, }_{t}^{{fit}}\) as regressor of interest and factoring out deterministic component \({\mu }_{{fit}}+{\lambda }_{{fit}}{d}_{t}\) (shown on the plot) along with other variables of no interest, including RTs, response switches, and RL variables (**p = 0.0021, ***p = 0.00025; one-sample two-sided T-tests, d.f. = 21). Error bars are s.e.m. across participants. dmPFC activity correlated negatively at outcome time and positively at choice time with best-fitting realizations \({U}_{{fit}}^{t}\) of Weber variability stochastic component \({u}_{t}\). Data points show individual subjects’ data. See supplementary Fig. 5 for additional analyses regarding individual data. Source data are provided as a Source Data file.
