Atari-style video game learning fMRI

Atari-style video game learning fMRI ========== This dataset contains behavioral and functional MRI (BOLD) data from 32 human subjects learning to play different Atari-style games. Additionally, it includes code for analyzing the data using two different models: * Explore, Model, Plan Agent (EMPA): a theory-based reinforcement learning agent (see [Tsividis et al. (2021)](https://arxiv.org/abs/2107.12544v1)), * Double Deep Reinforcement Learning network (DDQN): a deep reinforcement learning agent (see [van Hasselt et al. (2015)](https://arxiv.org/abs/1509.06461)) This dataset was collected for the following paper: * [Tomov, M.S., Tsividis, P.A., Pouncy, T., Tenenbaum, J.B., & Gershman, S.J. (2022). The neural architecture of theory-based reinforcement learning.](https://www.biorxiv.org/content/10.1101/2022.06.14.496001v1) For more information, see the Methods section of the paper.