Unfold Documentation
If you want to follow the tutorials, best to start with the mass-univariate approach, which should be familiar to you if you did ERPs before. Then the overlap-correction tutorial, mixed mass univariate, mixed overlap (tricky!). If you are then not satisfied, check out more advanced topics: effects-interface (aka what to do after fitting), or non-linear effects.
In case you want to understand the tools better, check out our explanations.
Once you are familiar with the tools, check out further how-to guides for specific applications.
In case you want to understand the toolbox better, we plan to offer technical references. This includes Benchmarks & Explorations.
Quick start
There are four main model types
- Timeexpansion No, Mixed No :
fit(UnfoldModel, [Any=>(f, -0.1:0.01:0.5)], evts, data_epoch)
- Timeexpansion Yes, Mixed No :
fit(UnfoldModel, [Any=>(f, basisfunction)], evts, data)
- Timeexpansion No, Mixed Yes :
fit(UnfoldModel, [Any=>(fLMM, -0.1:0.01:0.5)], evts, data_epoch)
- Timeexpansion Yes, Mixed Yes:
fit(UnfoldModel, [Any=>(fLMM, basisfunction)], evts, data)
f = @formula 0 ~ 1 + condition
fLMM = @formula 0 ~ 1 + condition + (1|subject) + (1|item)
basisfunction = firbasis(τ = (-0.1,0.5), sfreq = 100))