rERP	EEG visualisation	EEG Simulations	BIDS pipeline	Decode EEG data	Statistical testing

Sub/Wrapper-Package of Unfold.jl. Ultimately it should provide the means to automatically load a Dataset in BIDS format and apply unfold-style processing to it.

Install

Installing Julia

Click to expand

The recommended way to install julia is juliaup. It allows you to, e.g., easily update Julia at a later point, but also test out alpha/beta versions etc.

TL:DR; If you dont want to read the explicit instructions, just copy the following command

Windows

AppStore -> JuliaUp, or winget install julia -s msstore in CMD

Mac & Linux

curl -fsSL https://install.julialang.org | sh in any shell

Installing Unfold

using Pkg
Pkg.add("UnfoldBIDS")

Quickstart

using UnfoldBIDS


# To look up the paths of all subjects and store in a Dataframe:
layout_df = bids_layout(bidsPath::AbstractString; # Path to BIDS root folder
                        derivatives::Bool=true, # Do you want to us the derivative/ processed data? Default = true
                        specificFolder::Union{Nothing,AbstractString}=nothing, # If you want a specific folder in derivatives or root specify here
                        excludeFolder::Union{Nothing,AbstractString}=nothing, # You can exclude specific folders when not looking for a specific sub-folder 
                        ses::Union{Nothing,AbstractString}=nothing, # Specify session; will load all sessions if not specified
                        task::Union{Nothing,AbstractString}=nothing, # Specify task; will load all tasks if not specified
                        run::Union{Nothing,AbstractString}=nothing) # Specify run; will load all runs if not specified

# To load all data into memory/ one dataframe:           
eeg_df = load_bids_eeg_data(layout_df; verbose::Bool=true, kwargs...)

# To run Unfold model:
models_df = run_unfold(dataDF, bfDict; eventcolumn="event",removeTimeexpandedXs=true, extract_data = raw_to_data, verbose::Bool=true, kwargs...)

# For dataframe containing tidy results
results_df = bids_coeftable(models_df)

# To unpack results into one big tidy DataFrame, with subject information
results = unpack_results(results_df)

Note: The specificFolder option will look for the folder either in the root (i.e. provided bidsPath -> bidsPath/specificFolder) or in the derivative (i.e. bidsPath/derivatives -> bidsPath/derivatives/specificFolder) based on the derivative flag!

Supported EEG file types

• edf
• vhdr
• fif
• set

Contributions

Contributions are very welcome. These could be typos, bugreports, feature-requests, speed-optimization, new solvers, better code, better documentation.

How-to Contribute

You are very welcome to raise issues and start pull requests!

Adding Documentation

1. We recommend to write a Literate.jl document and place it in docs/literate/FOLDER/FILENAME.jl with FOLDER being HowTo, Explanation, Tutorial or Reference (recommended reading on the 4 categories).
2. Literate.jl converts the .jl file to a .md automatically and places it in docs/src/generated/FOLDER/FILENAME.md.
3. Edit make.jl with a reference to docs/src/generated/FOLDER/FILENAME.md.

Contributors

Benedikt Ehinger 🐛 💻 📆 🤔

René Skukies 👀 🤔 💻 🐛

This project follows the all-contributors specification.

Contributions of any kind welcome! You can find the emoji key for the contributors here

Citation

Acknowledgements

Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany´s Excellence Strategy – EXC 2075 – 390740016