Directory structure

After downloading everything, your directory structure should look like this (N.B. this is just a sketch; does not include every single file):

sacc-tDCS
│   README.md [this file]
│   analysis.m [GitHub]
│   sacc-tDCS.md [GitHub]
|   sacc-tDCS.nb.html [OSF]
│   sacc-tDCS.Rmd [GitHub]
│   sacc-tDCS.Rproj [GitHub]
│
└───data [figshare]
│   │   FEF_coords.csv
│   │   FEF.node
│   │   PANAS.csv
│   │   reflection.csv
│   │   sacc-tDCS_data.csv
│   │   sacc-tDCS_quantiles.csv
│   │   session_info.csv   
│   │   subject_info.csv
│   │   tdcs_sensations.csv
│   │
│   └───S01
│   │   │   sacc_tDCS*.asc [24 of these]
│   │   └───raw
│   │       │   sacc_tDCS*.edf [24 of these]
│   │       │   *main.mat [2 of these]
│   │       │   *practice.mat [2 of these]
│   └───S02
│       │  ...
│   
└───doc [OSF]
│   │   participant_log.csv
│   │
│   └───questionnaires
│   └───tDCS_blinding
│   
└───neuronav [OSF]
│   
└───docs
│   │   median_latency.Rmd [GitHub]
│   │   median_latency.nb.html [OSF]
│   │   median_latency.md [GitHub]
│   │   ...
│   └───median_latency_files [GitHub]
│   │   ...
│   │   index.html [GitHub]
│   │   sacc-tDCS_paper.html [GitHub]
│   │   sacc-tDCS.nb.html [GitHub]
│   └───figures [GitHub]
│   └───site_libs [GitHub]

└───site
│   │   _site.yml [GitHub]
│   │   badges.png [Github]
│   │   index.Rmd [GitHub]
│   │   sacc-tDCS_paper.Rmd [GitHub]
│   │   sacc-tDCS.bib [GitHub]
│   │   ...
│   └───figures
│   
└───src [GitHub]
│   │
│   └───bin
│   └───func
│   └───lib
│   
└───task [GitHub]

File descriptions

• sacc-tDCS.Rmd: R notebook with analysis code that will reproduce all of the results, figures and statistics contained in the paper. See the notebooks folder for additional notebooks with a more in-depth exploration of the dataset.
• sacc-tDCS.nb.html: HTML Output of the notebook, meant for viewing in any browser.
• sacc-tDCS.md: Markdown output of the notebook, optimized for rendering on GitHub. Plots referenced in the .md file are contained in sacc-tDCS_files/.
• sacc-tDCS.Rproj: Config file with options for the R project; also determines top-level folder.
• analysis.m: MATLAB script that loads the raw data and creates the .csv file that’s read in by the R notebook. See data/README.md for more info on the in- and outputs of this script.
• install.R and runtime.txt: configuration files for running the notebooks remotely with Binder.

Folder descriptions

N.B. Each folder has its own README.md file with more detailed information on its contents.

• data/: All the raw and processed data collected during this project.
• doc/: Metadata and additional materials.
• neuronav/: Contains (previously existing) MRI (meta)data.
• docs/: Additional notebooks with more in-depth analyses on each different aspect of the project. More information can be found in the notebooks themselves; they are also referred to in the main sacc-tDCS notebook. Like the main notebook, each has three types of files (.Rmd, nb.html and .md) and a folder with plots. The html files are what this website consists of.
• site/: Some other source files for building this website.
• src/: All other analysis code used in the project.
• task/: Code for the experimental task and control of the eye tracker; used during data collection.

Starting from the raw data

1. Make sure you’ve downloaded and unzipped all the individual subject data (i.e. the folders starting with S) from figshare, and that they’re placed in the data folder (as outline in the Directory structure section).
2. Make sure you’ve downloaded all the code in the src folder from GitHub.
3. Place the analysis.m file in the top-level folder (i.e. the one containing data and src), and run it in MATLAB. When the script is finished, you should have generated the sacc-tDCS_data.csv file in the data folder.

Note that this file is already available on figshare (and running the analysis.m script should recreate it exactly), so it is not necessary to start from this step.

Starting from the processed data

1. Make sure you’ve downloaded all the .csv files from figshare, and that they’re placed in the data folder (as outline in the Directory structure section).
2. Make sure you’ve downloaded all the code in the src folder from GitHub.

• Place the sacc-tDCS.Rmd file ). Open the sacc-tDCS.Rmd (in the in the top-level folder, i.e. the one containing data and src) in RStudio and run it to reproduce all the figures, results and statistics in the paper (if you don’t have RStudio, you can still run the R code in the notebook, but you might have to copy-paste individual code sections, because there is also a lot of text in the notebooks).
• Run any of the other notebooks in the docs folder to see the results of all additional data exploration / analyses we did. Or simply open up the .nb.html or .md files to see the results without having to run the code.

Alternatively, follow this link to create a remote RStudio session in your browser with Binder:

This will already set everything up for you on the server, including all packages that the analysis code depends upon. You can then run the notebooks from the comfort of your own browser (as described above).