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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

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('eventtypes',{'fixation'},'formula','y ~ 1+ cat(stimulusType)*cat(color)')
EEG = uf_timeexpandDesignmat('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