• Home
• Download from Github
• • Getting Started
    • Unfold’s toolbox workflow
    • Massive univariate modeling (rERP)
    • Artefacts & missing data/predictors
      • Removing artifactual data
      • Imputation of missing data
  • Theoretical Background
    • Introduction to linear modeling
    • Why deconvolution?
    • How does deconvolution work?
    • Introduction to additive/spline linear modeling
    • The connection of (formal) convolution and timeexpansion
  • Tutorials / Examples
    • Quickstart: 2x2 ANOVA
    • Longstart: 2x2 ANOVA
    • Non-Linear Predictors using splines
    • With and without deconvolution
    • Time-Basis functions
    • 2nd level (group/subject) statistics
    • Single trial ERPimages
    • Temporal Response Functions (TRFs)
    • Analysis from the PeerJ paper
  • Function Documentation
    • Essential functions
    • Data cleaning
    • Massive univariate linear modelling
    • Designmatrix-Tools
    • Post-Fit tools
    • Plotting
      • plot events & designmatrix
      • plot results
  • Data Structures
    • Minimal Data Specifications
    • Fields of EEG.unfold()
    • Fields of ufresult()
    • Fields of unfold.splines()