Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans
Learning rates computed from each of our regions of interest, overlaid on the learning rates fit to reaction time behavior. The best-fitting learning rates are displayed for each type of trial: sequential image-identification trials, decision trials, and choice outcome trials. For learning trials in hippocampus and caudate, learning rates are computed using the forward entropy regressor. For learning trials in face- and house-selective cortex, learning rates are computed using the estimated probability of the image appearing on the next trial. For decision trials in hippocampus, learning rate is computed using the choice difficulty regressor. For decision trials in face- and house-selective cortex, learning rates are computed using the portion of the choice difficulty regressor specific to that image. For outcome trials in nucleus accumbens, learning rate is computed using the reward prediction error regressor. Error bars: 1 SEM.