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

A toolbox for visualizations of EEG/ERP data and Unfold.jl models.

Based on three libraries

• Unfold - for performing deconvolution regression;
• Makie - very flexible visualisation library (Maki-e means "visualisation" on Japanese);
• Algebra of Graphics - Makie-based visualisation library, allowing flexible mapping.

This grants users high performance, and highly customizable plots.

We currently support 9 general ERP plots:

• ERP plots
• Butterfly plots
• Topography plots
• Topography time series
• ERP grid
• ERP images
• Channel images
• Parallel coordinates
• Circular topoplots

And 2 Unfold-specific plots:

• Design matrices
• Splines plot

Install

Installing Julia

Installing Unfold

using Pkg
Pkg.add("UnfoldMakie")

Quickstart

using UnfoldMakie
using CairoMakie # backend
using Unfold, UnfoldSim # Fit / Simulation

data, evts = UnfoldSim.predef_eeg(; noiselevel = 12, return_epoched = true)
data = reshape(data, 1, size(data)...) # simulate a single channel

times = range(0, step = 1 / 100, length = size(data, 2))
m = fit(UnfoldModel, @formula(0 ~ 1 + condition), evts, data, times)

plot_erp(coeftable(m))

Contributions

Contributions are very welcome. These can be typos, bug reports, feature requests, speed improvements, new solvers, better code, better documentation.

How to Contribute

You are very welcome to submit 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.

Citation

If you use these visualizations, please cite:

Contributors

Benedikt Ehinger 🐛 💻 📖 🤔 🚇 🚧 💬 👀 ⚠️ ✅	Vladimir Mikheev 🐛 💻 📖 🤔 🚧 👀 ⚠️ ✅	Daniel Baumgartner 💻 📖	Niklas Gärtner 💻 📖	Soren Doring 💻 📖	Fadil Furkan Lokman 💻 📖	Judith Schepers 🐛 🤔 📖
René Skukies 📖

Acknowledgements

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 251654672 – TRR 161” / “Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) – Projektnummer 251654672 – TRR 161.

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