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EEGLAB roadmap

Learn EEGLAB step by step, from the raw file to group results.

Start here: Where the EEG signal comes from62 lessons in 11 stations. Start with the core ones, add what you need.
  • Core
  • Recommended
  • Optional

Hover over a lesson, or move to it with the keyboard, to see what it builds on.

Each lesson lists what it builds on at the top, under "Before this lesson".

  1. CH 00

    Before you start

    5 lessons · 65 min
    1. Where the EEG signal comes from
    2. The 10-20 system & electrodes
    3. MATLAB basics for EEGLAB
    4. Signals & frequencies
    1. Designing EEG experiments
  2. CH 01

    Getting to know EEGLAB

    6 lessons · 66 min
    1. Installing EEGLAB & plugins
    2. The EEGLAB window & menus
    3. The EEG structure
    1. ALLEEG & dataset management
    2. .set and .fdt files
    3. Merging & selecting data
  3. CH 02

    Importing data

    4 lessons · 54 min
    1. Importing raw files: EDF, BDF & BrainVision
    2. Channel locations
    3. Events
    1. BIDS & OpenNeuro data
  4. CH 03

    Preprocessing

    7 lessons · 92 min
    1. Resampling
    2. High-pass & low-pass filtering
    3. Removing line noise (50/60 Hz)
    4. Bad channels
    5. Channel interpolation
    6. Re-referencing
    1. clean_rawdata & ASR
  5. CH 04

    ICA & artifact cleaning

    7 lessons · 91 min
    1. ICA, simply explained
    2. Running ICA
    3. 1-Hz filtering for ICA & copying weights
    4. ICLabel & removing components
    5. Reading artifact components
    1. How much data ICA needs
    2. AMICA & Picard
  6. CH 05

    Epoching

    3 lessons · 37 min
    1. Extracting epochs
    2. Baseline correction
    3. Rejecting bad epochs
  7. CH 06

    Analysis

    5 lessons · 69 min
    1. ERPs & averaging
    2. Power spectrum (PSD)
    1. ERPLAB: measuring amplitude & latency
    2. Time-frequency: ERSP & ITC
    3. Data quality (SME)
  8. CH 07

    Plotting & figures

    4 lessons · 48 min
    1. Scalp maps (topoplot)
    2. Plotting channel ERPs
    1. ERP image
    2. Publication-ready figures
  9. CH 08

    Group analysis (STUDY)

    10 lessons · 139 min
    1. What a STUDY is and when you need one
    2. Creating a STUDY
    3. STUDY designs & variables
    4. Precomputing measures
    5. Plotting group channel measures
    6. Statistics & multiple comparisons
    1. Creating a STUDY from BIDS
    2. Exporting results for papers & stats software
    3. IC clustering
    4. LIMO EEG
  10. CH 09

    Scripting & automation

    6 lessons · 79 min
    1. eegh & the command history
    2. A single-subject script
    1. Batch processing
    2. Automated pipelines: when to use them
    3. Organizing files & storage
    4. Running on HPC
  11. CH 10

    Advanced topics

    5 lessons · 72 min
    1. Source localization with DIPFIT
    2. Connectivity with SIFT
    3. Decoding (MVPA)
    4. Writing an EEGLAB plugin
    5. MNE-Python & FieldTrip compared