A toolbox for deconvolution of overlapping EEG (Pupil, LFP etc.) signals and (non)-linear modeling
We recently published a new preprint on the analysis of Eyetracking/EEG data, with unfold playing a prominent role Dimigen & Ehinger 2019
If you use the toolbox, please cite us as: Ehinger BV & Dimigen O, Unfold: An integrated toolbox for overlap correction, non-linear modeling, and regression-based EEG analysis, peerJ, https://peerj.com/articles/7838/
Adjust for overlap between subsequent potentials using linear deconvolution
Massive-Univarite Modeling (rERP) using R-style formulas, e.g.
Non-linear effects using regression splines (GAM), e.g.
Model multiple events, e.g. Stimulus, Response and Fixation
Use temporal basis functions (Fourier & Splines)
(Optional) regularization using glmnet
Temporal Response Functions (TRFs)
A new addon unmixed, allowing to use mixed models can be found in its alpha version version here
Continuous data in EEGLAB 12+ format
Unfold toolbox Download it on GitHub
To get started, best is to start with the 2x2 ANOVA-Design tutorial Quickstart: 2x2 ANOVA