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A matlab EEG toolbox to perform overlap correction and non-linear & linear regression.

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unfoldtoolbox/unfold

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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

Note

Have a look at theUnfold.jl Julia ecosystem which includes all the latest features, bugfixes and more. Unfold-Matlab is not actively developed, only bugfix releases are provided. PRs for new features are definitely welcome!

Getting help

📢Try out ourdiscussion forum - we often get questions via email, a more transparent and open way is to use thegithub discussions feature

Installation

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

Running

run('init_unfold.m')

Simple example

Check out thetoolbox 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

In addition, consider also citing the following reference, which illustrates the possibilites and options of unfold for a specific application example:

Dimigen O, Ehinger BV: "Regression-based analysis of combined EEG and eye-tracking data: Theory and applications. Journal of Vision, 21(1), 3-3",https://jov.arvojournals.org/article.aspx?articleid=2772164

Research notice

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

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

For more information, please visitour informational page or download ourparticipant information sheet.


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