We then tested how activity that parametrically tracked the increase in CPV correlated with individual ToM scores during bubble markets and nonbubble markets, calculating Spearman’s rank correlation coefficient between the parameter estimates in dmPFC and ToM scores. For the analysis using the PID, we calculated this metric (as described in the Results) for each time point in the original markets used as stimuli for the fMRI study. We then averaged the PID over the period of movie observed by each participant and used this parameter in a new GLM. We then contrasted this parametric regressor find more in the bubble markets versus the nonbubble markets and extract

activity of two ROIs of 8 mm sphere centered in dmPFC [9, 50, 28] and vmPFC [3, 53, −2]. To assess changes in connectivity between dmPFC and vmPFC as a function of the market type, we carried out a psychophysiological interaction (PPI) analysis. PPI is a measure of context-dependent connectivity, explaining the regional activity of other brain regions (here vmPFC) in terms of the interaction between responses in a seed region (here dmPFC) and a cognitive or sensory process. We carried out PPI analysis using the generalized PPI toolbox for SPM (gPPI; http://www.nitrc.org/projects/gppi). gPPI creates a new GLM in which the deconvolved activity of the seed region (8 mm sphere centered

in dmPFC [9, 50, 28]) is assigned to the regressors modeling the effect of the task at the time of the trading periods and reconvolved Gemcitabine with the hemodynamic response function. Average time courses were extracted from all voxels within an 8 mm sphere surrounding the vmPFC peak coordinate [3, 53, −2] that we isolated in the original SPM analysis. This was done since the aim of this analysis was to demonstrate that the activity we isolated in dmPFC and vmPFC (in the main SPM contrast) showed a functional connectivity. The main effects of the task, seed region time course, and motion parameters were included as regressors of no interest. The PPI contrast compares bubble markets (+1) with

nonbubble markets (−1). Second-level group contrasts from our GLM were calculated as a one-sample t test against zero for each first-level linear contrast. Activations were reported as significant if they survived familywise error correction (FWE) for multiple to comparisons across a volume of 8 mm (SVC) cantered on peak of activity isolated in independent studies. For vmPFC, we used the coordinates [0, 53, 4] taken from (Suzuki et al., 2012); for dmPFC, we used the coordinates [−3, 51, 24] taken from (Hampton et al., 2008). Thanks to David Porter for sharing the behavioral data, Antonio Rangel for help during the initial design of the experiment, and Jessica Hughes for commenting on the manuscript. Support came from the Sir Henry Wellcome Fellowship (B.D.M.), the Betty and Gordon Moore Foundation (C.F.C., J.O.