Statistical learning shapes pain perception and prediction independently of external cues
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Description
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
Files
tsl_elife_24.zip
Files
(10.1 GB)
| Name | Size | Download all |
|---|---|---|
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md5:96aabd75e78968f81bf508629b1dc5d1
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10.1 GB | Preview Download |
Additional details
Software
- Repository URL
- https://github.com/nox-lab/tsl_elife_24