Evidence for Model-based Computations in the Human Amygdala during Pavlovian Conditioning
Contemporary computational accounts of instrumental conditioning have emphasized a role for a model-based system in which values are computed with reference to a rich model of the structure of the world, and a model-free system in which values are updated without encoding such structure. Much less studied is the possibility of a similar distinction operating at the level of Pavlovian conditioning. In the present study, we scanned human participants while they participated in a Pavlovian conditioning task with a simple structure while measuring activity in the human amygdala using a high-resolution fMRI protocol. After fitting a model-based algorithm and a variety of model-free algorithms to the fMRI data, we found evidence for the superiority of a model-based algorithm in accounting for activity in the amygdala compared to the model-free counterparts. These findings support an important role for model-based algorithms in describing the processes underpinning Pavlovian conditioning, as well as providing evidence of a role for the human amygdala in model-based inference.
Additional Information© 2013 Prevost et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received July 3, 2012; Accepted December 27, 2012; Published February 21, 2013. We thank Simon Dunne for helpful assistance. Author Contributions: Conceived and designed the experiments: CP JPOD. Performed the experiments: CP. Analyzed the data: CP DM RKJ PB. Contributed reagents/materials/analysis tools: PB. Wrote the paper: CP DM PB JPOD. Funding: This work was funded by Science Foundation Ireland grant 08/IN.1/B1844 to JPOD. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Published - journal.pcbi.1002918.pdf