The code in this repository reproduces most analyses and figures from Tomassini et al.,2019 'Learning from the past and expecting the future in Parkinsonism: Dopaminergic influence on predictions about the timing of future events' published in Neuropsychologia: https://doi.org/10.1016/j.neuropsychologia.2019.02.003. Model fitting is implemented on iPython using the Hierarchical Drift-Diffusion Modelling toolbox (https://github.com/hddm-devs/hddm). Each model tested in the paper is implemented on a separate Jupyter notebook. Please note that model fitting will require a long time (approx 15 hours on a Mac Pro with 4 CPUs). Estimated model parameters (including DICs) are reported in Stats_Model#.txt files.
For details regarding the motivation behind analyses and the interpretation of results, see the manuscript.