**Please read to find information about the content and the structure of this repository, where to find the files you are looking for and notes on reproducibility.** *Note: Make sure to also read the file "software_requirements.txt" when aiming to reproduce the results of this project.* ### **Overview:** This repository contains all data, analysis scripts, model files and experimental software related to the article *Repetition Learning: Neither a Continuous Nor an Implict Process*. To learn more about the structure of the project and where to find what, please continue reading. ### **Structure:** The repository is split into the main project component (*Data, Materials, and Code for: Repetition Learning: Neither a Continuous Nor an Implicit Project*) and a Sub-Component which contains large files of our fitted Bayesian models (*Stanfit Model Objects*): - The *main project component* contains all data, analysis scripts, experimental software and model results for the related article. You can export this component if you want to reproduce the main results of the study or look into the data or the experimental software. Please note, that selected scripts are not fully reproducible in itself because they depent on files stored in the "Stanfit Model Objects" COmponents - The *Stanfit Model Object* Sub-Component stores the full output of all fitted Bayesian models and the predicted trial-by-trial values for each participant from the models. These files have been separated from the main project because of their large size. We don't want to force users to export a project of ~30 GB just to reproduce simple analyses which are not dependent on the model files, but still want to share these files. The files are only necessary to reproduce the parameter extractions from the fitted models and to plot the predictions of the different models on the observed data. The outputs of the prediction plots are provided as HTML documents. In the main part of the project, all files are related to the overall R-project. We recommend to export the full project to make sure that all file paths are correctly related to each other. The current version of the **preprint** and the related **supplementary materials** can be found in the *paper* folder. ### **Data:** All data uploaded to this project was anonymized prior to upload. Thus, the uploaded raw data was already slightly processed. Processing only included exclusion of incomplete data sets and separation of experimental data and personal participant information. No personla participant information has been uploaded to this repository. We provide the R-script which we used for the initial processing to show all modifications we did to the raw data. Data is provided in a non-aggregated way. Descriptions and all codebooks for all data sets are included with the data sets. ### **Reproducibility Notes:** All main analyses and results reported in the article can be reproduced from the main project. However, please note that for some scripts, the download of additional files is necessary which are store separately in the *"Stanfit Model Objects"* Sub-Component of this repository because of their large size. Model files can be downloaded separately if necessary. Reproducibility notes and instructions on which file to download are provided in the corresponding scripts if applicable. ### **Where to find what?** #### **Main Project Component:** The main project is structured into the two experiments reported in the article. *experiment1_awareness-in-visual-hebb* contains all data, files and analyses related to the visual experiment reported in the article. *experiment2_replication-classic-hebb-task* contains all data, files and analyses related to the verbal experiment reported in the article. Both experiments have the same file structure: **analyses**: contains all analysis scripts, model scripts and model results. The folder itself contains different subfolders: - *models:* contains the stan model scripts for fitting the models (stan_models) and the extracted parameters form the fitted stan models (stan_fits.nosync). The stanfit objects itself are outsourced into the Sub-Component "Stanfit Model Objects". The extracted model parameters are sorted into different subfolders, corresponding to the different model versions (learning-onset-models, combined-learning-awareness-models, continuous-learning-model). - *fits-learning-onset:* contains the scripts for fitting the learning-onset model to the three experimental conditions, a script for analysing the model results and the outputs of plotting the model predictions to every individual participant. - *fits-multivariate-model:* contains the scripts for fitting the multivariate learning + awareness model to Awareness Rating condition, a script for analyzing the results of this model and the outputs of plotting the model predictions for learning and awareness for every individual participant. - *fits-continuous:* contains the scripts for fitting the alternative continuous-learning model, a script for comparing the continuous-learning and the variable-onset model and the outputs for plotting the model predictions of the continuous learning model for every individual participant. - *functions-local:* contains local copies for the custom functions used in the analysis scripts. In the analysis scripts, custom functions are loaded from Github. **data:** contains all data files and codebooks related to the experiment. **expfiles:** contains everything related to the experimental software. All experiments were programmed using the online experiment builder lab.js. The .json files corresponds to the implementation of the experiment in lab.js and can be uploaded in the lab.js online builder. The "data-collection" folder contains and exported version of the experiment which was used to host the experiment on a Jatos server. Instructions for the experiment were created in power-point and are included in the "instructions" folder. Custom javascript functions for the experiment are in the "JS-functions" folder. **plots:** contains plots created from the experimental data. **preregistration:** contains the preregistration files. #### **Stanfit Model Objects Sub-Component:** The Sub-Component for the fitted model files is also structured into the two experiment. *experiment1_awareness-visual-hebb-learning* contains the fitted model objects from the visual experiment reported in the article. *experiment2_replication-classic-hebb-task* contains the fitted model objects from the verbal experiment reported in the article. Both experiment-folder contain three subfolders for the corresponding models: - learning-onset-models: Contains the fitted stan models and the model prediction files from the variable onset-model fitted to the working memory data of the three between subject conditions. - continuous-models: Contains the fitted stan models and the model prediction files from the continuous-learning-model fitted to the working memory data of the three between subject conditions. - combined-learing-awareness-model: contains the fitted stan model and the model predictions files from the multivariate model fitted to the working memory and the awareness rating data of the Awareness Rating condition. ### **Contact:** If you run into any issues with the provided scripts, are not able to reproduce results or cannot find what you are looking for, please contact me and I will try to do my best to help you out: _philipp.musfeld@psychologie.uzh.ch_