Skip to main content

This lesson introduces the EEGLAB toolbox, as well as motivations for its use.

Difficulty level: Beginner
Duration: 15:32
Speaker: : Arnaud Delorme

In this lesson, you will learn about the biological activity which generates and is measured by the EEG signal.

Difficulty level: Beginner
Duration: 6:53
Speaker: : Arnaud Delorme

This lesson goes over the characteristics of EEG signals when analyzed in source space (as opposed to sensor space). 

Difficulty level: Beginner
Duration: 10:56
Speaker: : Arnaud Delorme

This lesson describes the development of EEGLAB as well as to what extent it is used by the research community.

Difficulty level: Beginner
Duration: 6:06
Speaker: : Arnaud Delorme

This lesson provides instruction as to how to build a processing pipeline in EEGLAB for a single participant. 

Difficulty level: Beginner
Duration: 9:20
Speaker: :

Whereas the previous lesson of this course outlined how to build a processing pipeline for a single participant, this lesson discusses analysis pipelines for multiple participants simultaneously. 

Difficulty level: Beginner
Duration: 10:55
Speaker: : Arnaud Delorme

In addition to outlining the motivations behind preprocessing EEG data in general, this lesson covers the first step in preprocessing data with EEGLAB, importing raw data. 

Difficulty level: Beginner
Duration: 8:30
Speaker: : Arnaud Delorme

Continuing along the EEGLAB preprocessing pipeline, this tutorial walks users through how to import data events as well as EEG channel locations.

Difficulty level: Beginner
Duration: 11:53
Speaker: : Arnaud Delorme

This tutorial demonstrates how to re-reference and resample raw data in EEGLAB, why such steps are important or useful in the preprocessing pipeline, and how choices made at this step may affect subsequent analyses.

Difficulty level: Beginner
Duration: 11:48
Speaker: : Arnaud Delorme

This tutorial instructs users how to visually inspect partially pre-processed neuroimaging data in EEGLAB, specifically how to use the data browser to investigate specific channels, epochs, or events for removable artifacts, biological (e.g., eye blinks, muscle movements, heartbeat) or otherwise (e.g., corrupt channel, line noise). 

Difficulty level: Beginner
Duration: 5:08
Speaker: : Arnaud Delorme

This tutorial provides instruction on how to use EEGLAB to further preprocess EEG datasets by identifying and discarding bad channels which, if left unaddressed, can corrupt and confound subsequent analysis steps. 

Difficulty level: Beginner
Duration: 13:01
Speaker: : Arnaud Delorme

Users following this tutorial will learn how to identify and discard bad EEG data segments using the MATLAB toolbox EEGLAB. 

Difficulty level: Beginner
Duration: 11:25
Speaker: : Arnaud Delorme

This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

Difficulty level: Intermediate
Duration: 1:40:52
Speaker: : Paul Triebkorn

This module covers many of the types of non-invasive neurotech and neuroimaging devices including electroencephalography (EEG), electromyography (EMG), electroneurography (ENG), magnetoencephalography (MEG), and more. 

Difficulty level: Beginner
Duration: 13:36
Speaker: : Harrison Canning

This lecture covers a wide range of aspects regarding neuroinformatics and data governance, describing both their historical developments and current trajectories. Particular tools, platforms, and standards to make your research more FAIR are also discussed.

Difficulty level: Beginner
Duration: 54:58
Speaker: : Franco Pestilli

This short video walks you through the steps of publishing a dataset on brainlife, an open-source, free and secure reproducible neuroscience analysis platform.

Difficulty level: Beginner
Duration: 1:18
Speaker: :

This video shows how to use the brainlife.io interface to edit the participants' info file. This file is the ParticipantInfo.json file of the Brain Imaging Data Structure (BIDS).

Difficulty level: Beginner
Duration: 0:34
Speaker: :

This video will document the process of running an app on brainlife, from data staging to archiving of the final data outputs.

Difficulty level: Beginner
Duration: 3:43
Speaker: :

This video will document the process of visualizing the provenance of each step performed to generate a data object on brainlife.

Difficulty level: Beginner
Duration: 0:21
Speaker: :

This video will document the process of downloading and running the "reproduce.sh" script, which will automatically run all of the steps to generate a data object locally on a user's machine.

Difficulty level: Beginner
Duration: 3:44
Speaker: :