21:04

What is the optimal automated EEG pipeline?

16:59

What is the best ERP baseline?

18:21

What is the best EEG reference?

15:00

A FieldTrip EEG automated processing pipeline

26:17

A Brainstorm EEG automated processing pipeline

25:32

An MNE EEG automated processing pipeline

09:41

Process EEG data in EEGLAB then build an automated pipeline

08:33

EEGLAB on high performance computing ressources

22:58

From raw EEG to BIDS in 2 minutes

26:14

Learning to recognize ICA components of EEG and mobile EEG

41:16

Exporting data using the BIDS EEGLAB plugin - live coding session

19:14

16 advices for conducting electro-encephalography experiments

08:59

The Lab Streaming Layer (LSL)

07:14

EEGLAB versions

15:02

Robust statistics applied to EEG data #5: Correction for multiple comparisons

05:07

Robust statistics applied to EEG data #4: Bootstrap vs Permutation

16:15

BIDS data format for Neuroimaging: Export/Import BIDS EEG data from EEGLAB

20:55

The BIDS Neuroimaging Data Format for EEG

09:10

Robust statistics applied to EEG data #3: The Bootstrap Approach

06:52

Robust statistics applied to EEG data #2: increasing robustness

11:46

Robust statistics applied to EEG data #1: Basic inferential statistics

17:27

General Linear Modeling of EEG in EEGLAB/LIMO part 2: Practicum

18:48

General Linear Modeling of EEG in EEGLAB/LIMO part 1: Basic Theory

16:20

From raw data to group level analysis in EEGLAB

08:55

Time-Frequency Analysis of EEG Time Series Part 5: Practicum in EEGLAB

05:53

Time-Frequency Analysis of EEG Time Series Part 4: Inter-Trial Coherence (ITC)/Phase locking factor

11:08

Time-Frequency Analysis of EEG Time Series Part 3: Wavelet Transforms

09:06

Time-Frequency Analysis of EEG Time Series Part 2: EEG Spectrum and ERSP

08:49

Time-Frequency Analysis of EEG Time Series Part 1: Fourier Analysis of EEG Signal

06:53

ICA applied to EEG part 11: Common misconceptions about ICA and conclusion

05:47

ICA applied to EEG part 10: Looking at brain components

05:24

ICA applied to EEG part 9: Automatically detecting ICA component classes

07:04

ICA applied to EEG part 8: Removing Artifactual Components in EEGLAB

11:56

ICA applied to EEG part 7: Running ICA in EEGLAB and visualizing components

07:45

ICA applied to EEG part 6: Reproducibility of ICA decompositions

14:06

ICA applied to EEG part 5: Source localization of ICA components

10:21

ICA applied to EEG part 4: Removing ICA component artifacts in EEG data

08:17

ICA applied to EEG part 3: ICA applied to EEG data

07:50

ICA applied to EEG part 2: How does Infomax ICA work?

06:36

ICA applied to EEG: What is ICA?

10:35

EEGLAB time-frequency decomposition Part 4: Inter-trial coherence

10:14

EEGLAB time-frequency decomposition Part 1: Time-frequency estimates

04:51

EEGLAB time-frequency decomposition Part 2: Estimating the spectrum using the pwelch method

11:16

EEGLAB time-frequency decomposition Part 3: Event related spectral perturbation

04:41

EEGLAB time-frequency decomposition Part 5: Multi-trial cross-coherence estimates

03:42

EEGLAB time-frequency decomposition Part 6: Nyquist, time-frequency topography and exercises

15:33

EEGLAB introduction part 1: Why EEGLAB

10:57

EEGLAB introduction part 3: Source resolved EEG brain dynamics

10:56

EEGLAB introduction part 6: Multi subject analysis and scripting

09:21

EEGLAB introduction part 5: Single subject processing pipeline

06:07

EEGLAB introduction part 4: EEGLAB history and usage statistics

06:54

EEGLAB introduction part 2: The origin of the EEG signal

05:33

Processing Muse data with EEGLAB Part IV: Statistical analysis

22:15

Processing Muse data with EEGLAB Part III: Analysis of multiple data files

11:24

Processing Muse data with EEGLAB Part II: Artifact rejection

10:23

Processing Muse data with EEGLAB part I: Acquiring data

03:39

Installing the compiled version of EEGLAB (see description for download link)

18:07

Time-frequency decomposition in EEGLAB - see newer videos in description

01:04:11

Introduction to hierarchical GLM Statistics and Bootstrap by Cyril Pernet

39:06

Introduction to the EEGLAB STUDY and Study Design by Arnaud Delorme