Before revision:  Using a virtual lesioning approach ,  we identify which regions form the strongest neurophysiological drivers of these differences in learning rate . We complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses , providing evidence that higher dimensional responses also characterize patterns of activation within regions known to process and represent objects and their values .
After revision:  Using a virtual lesioning approach , we identify which regions form the strongest neurophysiological drivers of these differences in learning rate , and complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses , providing evidence that higher dimensional responses also characterize patterns of activation within regions known to process and represent objects and their values .