Statistical learning shapes pain perception and prediction independently of external cues

Dataset and code for the relevant analysis and results: "Statistical learning shapes pain perception and prediction independently of external cues" Onysk, J., Whitefield, M., Gregory, N., Jain, M., Turner, G., Seymour, B., Mancini, F. (2024). eLife. https://doi.org/10.7554/eLife.90634.2 1 - data_collection Contains the code for the psychophysical experiment (PsychToolBox), including the sequence generations scripts. 2 - preprocessing Contains code that preprocesses behavioural data from PsychToolBox. This includes linear transformation of inputs, exporting data to stan readable format and plotting Supplement figures. - The raw behavioural data can be found in preprocessing/data. Stan ready ready for each condition is found in preprocessing/stan_data 3 - model_fit_analysis Contains stan models used in the paper ('models/'), model fitting code ('fit_models_cs.R) (inlcuding HPC setup in 'hpc/'), initial analysis script for processing stan samples ('primary_analysis_cs.R'), as well as additional analyis scripts ('extra_analysis_cs.R', 'correlation_beh_model_cs.ipynb') that generate figures from the paper and supplement. - The posterior draws for parameters can be found in model_fit_analysis/output/cs_results 4 - model_recovery Contains code that execute model and parameter recovery analysis ('mp_recovery.R'), including HPC setup ('hpc/'). The 'mp_rec_analyse.R' reproduces model and parameter recovery results from the supplement. 5 - Figures Contains all the figures from the manuscript and the supplement. 6 - RDS_fits Contains RStan fit objects for each condition for each model