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Details on the different functions and usage can be found on the wiki pages here while this is a step by step tutorial.
Important notice
Whatever you display using LIMO, all the variables are returned in the workspace. For instance, if you plot all channels vs time (ERP results), then the raw statistical map and the significance mask are returned. If you plot a time course, that time course with confidence interval is returned, etc.
The tutorial is using Wakeman and Henson (2015) face data. In short, famous, unfamiliar and scrambled faces were presented, and repeated immediately or later. Subjects had to do a judgment task orthogonal to the design to keep them engaged. The EEG channels were extracted and preprocessed. Data can be found here.
This tutorial assumes you are using the lastest EEGLAB version that uses STUDY to link with LIMO tools.
More details on data and preprocessing can be found on the preliminaries page.
- getting the data
- preprocessing
- Within Subject Categorical Designs intro
- One way repeated measures ANOVA (Famous, Unfamiliar, Scrambled faces as conditions)
- One way repeated measures ANOVA revised (Famous, Unfamiliar, Scrambled faces as 1st level contrasts)
- Summary statistics to measure and report effects and effect sizes
- One sample t-test (contrasting Full Faces vs Scrambled Faces at the subject level)
- Summary statistics of differences
- Two-ways ANOVA (Faces x Repetition)
- Paired t-test (Famous vs Unfamiliar)