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UNFOLD - TOOLBOX

A toolbox for deconvolution of overlapping EEG signals and (non)-linear modeling

  • Linear deconvolution
  • Model specification using R-style formulas (EEG~1+face+age)
  • Programmed in a modular fashion
  • Spline regression
  • Regularization (using glmnet)
  • Temporal basis functions (Fourier & Splines)
  • Estimate temporal response functions (TRFs) for time-continuous predictors
  • Cross-validation

Getting help

📢 Try out our discussion forum - we often get questions via email, a more transparent and open way is to use the github discussions feature

Installation

git clone https://github.com/unfoldtoolbox/unfold
git submodule update --init --recursive --remote

Running

run('init_unfold.m')

Simple example

Check out the toolbox tutorials for more information!

EEG = tutorial_simulate_data('2x2')
EEG = uf_designmat(EEG,'eventtypes',{'fixation'},'formula','y ~ 1+ cat(stimulusType)*cat(color)')
EEG = uf_timeexpandDesignmat(EEG,'timelimits',[-0.5 1])
EEG = uf_glmfit(EEG)
% (strictly speaking optional, but recommended)
ufresult = uf_condense(EEG)
ax = uf_plotParam(ufresult,'channel',1);

Citation

Please cite as:

Ehinger BV, Dimigen O: "Unfold: An integrated toolbox for overlap correction, non-linear modeling, and regression-based EEG analysis", peerJ 2019, https://doi.org/10.7717/peerj.7838

Research notice

Please note that this repository is participating in a study into sustainability of open source projects. Data will be gathered about this repository for approximately the next 12 months, starting from June 2021.

Data collected will include number of contributors, number of PRs, time taken to close/merge these PRs, and issues closed.

For more information, please visit our informational page or download our participant information sheet.