Fig. 4: Brain activations associated with choice computations from corrupted beliefs.

A unique MRI bold activation cluster in the whole-brain analysis associated with choice computations at choice time, i.e., exhibiting jointly a negative linear effect \(\left(-({\widetilde{B}}_{{ch}}-{\widetilde{B}}_{{unch}})\right)\) and a positive quadratic effect \({({\widetilde{B}}_{{ch}}-{\widetilde{B}}_{{unch}})}^{2}\) of chosen-relative-to-unchosen beliefs undergoing Weber variability (dark blue, conjunction analysis, voxel-wise threshold p < 0.001, cluster-wise FWE-corrected p < 0.05); Linear and quadratic effects capture signed and unsigned differences respectively between chosen and unchosen beliefs (see text). Activations are superimposed on the MNI template sagittal and axial slices centered on the unsigned difference activation peak. B MRI activity at choice time averaged over the activation cluster shown in (A) plotted against chosen-relative-to-unchosen beliefs undergoing Weber variability and factoring out RTs and either the quadratic effect (left) or the linear effect (right). Note both the predicted negative linear effect and positive quadratic effect. C Full variance analyses at choice time over the activation cluster shown in (A) comprising the signed \({\widetilde{B}}_{{ch}}-{\widetilde{B}}_{{unch}}\) and unsigned \({({\widetilde{B}}_{{ch}}-{\widetilde{B}}_{{unch}})}^{2}\) differences between chosen and unchosen beliefs undergoing Weber variability, along with Weber variability (and with or without Reaction Times) as regressors. Data points show individual subjects’ data. Note that the Weber variability regressor captured no residual variances. Left graph: ***from left to right bars: p < 0.00001, p = 0.000038, p = 0.00007, p = 0.148; right graph: p < 0.00001, p = 0.000012, p = 0.138 (one-sample two-sided T-test, d.f. = 21). D Best-fitting realizations \({U}_{{fit}}^{t}\) of Weber variability stochastic components \({u}_{t}\) plotted against activation residuals averaged over the cluster shown in (A) and normalized by Weber variability deterministic component \({\mu }_{{fit}}+{\lambda }_{{fit}}{d}_{t}\). Activation residuals were computed from the regression analysis comprising Reaction Times and both \(\left(-({B}_{{ch}}-{B}_{{unch}})\right)\) and \({({B}_{{ch}}-{B}_{{unch}})}^{2}\) as regressors with Weber variability \({\epsilon }_{t}^{{fit}}\) removed from current beliefs when forming these regressors. The graph indicates that the best-fitting realizations \({U}_{{fit}}^{t}\) that corrupt beliefs driving choices reflected neural fluctuations, corrupting belief updating in the pre-SMA and ACC. All error bars are s.e.m. across participants. ***p < 0.001 (one-sample two-sided T-test, d.f. = 21). Source data are provided as a Source Data file.