Modeling of individual brain responses
Data were analyzed voxel-wise within the framework of the Generalized Linear Model (GLM) in a mass univariate manner. On single subject level, we modelled periods of anticipatory brain activity by means of box-car functions with an onset at the stop of the second cylinder and a width equal to the time gap between the second and third cylinder stop. To model the BOLD responses, these functions were convolved with the canonical hemodynamic response function (hrf) as implemented in SPM12 and served as regressors of interest in single-subject models. Additionally, regressors of no interest were constructed in the same way for the win, late loss, and early loss. On the single-subject level, the model contained separate regressors for gain anticipation (C1 = C2) and no gain anticipation (C1 ≠ C2) as well as the following regressors of no interest: gain (C1 = C2 = C3), loss (C1 = C2 ≠ C3), early loss (e.g., (C1 ≠ C2 = C3), button presses (after color bar changed to blue as well as green), visual flow (rotation of the wheels), and the six rigid body movement parameters. In addition, start and stop button presses were modelled by means of stick functions and convolved with the hrf. To account for the different amount in visual flow, we used the number of cylinders in motion convolved with the hrf as a related proxy (Lorenz et al. 