Figure 3.

Multivoxel pattern analysis. Figure illustrating the steps of the main multivoxel pattern analysis used in this study. A, Twelve feature sets of different time intervals were created for each participant. B, Recursive feature elimination (RFE) was used within each category for each feature set to obtain the 25% most informative voxels. C, The feature set with the highest within-category performance was used to perform across category predictions by training a model on one item category (e.g., snack foods) and using it to predict preferences over items of the other category (e.g., activities) and vice versa.