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Brief introduction to Research Resource Identifiers (RRIDs), persistent and unique identifiers for referencing a research resource. 

Difficulty level: Beginner
Duration: 1:30
Speaker: : Anita Bandrowski

This lecture provides an overview of successful open-access projects aimed at describing complex neuroscientific models, and makes a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

Difficulty level: Beginner
Duration: 1:00:39
Speaker: : Sharon Crook

This lesson provides an overview of Neurodata Without Borders (NWB), an ecosystem for neurophysiology data standardization. The lecture also introduces some NWB-enabled tools. 

Difficulty level: Beginner
Duration: 29:53
Speaker: : Oliver Ruebel

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 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 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 presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.

Difficulty level: Advanced
Duration: 50:28
Speaker: : Pierre Bellec
Course:

Neuronify is an educational tool meant to create intuition for how neurons and neural networks behave. You can use it to combine neurons with different connections, just like the ones we have in our brain, and explore how changes on single cells lead to behavioral changes in important networks. Neuronify is based on an integrate-and-fire model of neurons. This is one of the simplest models of neurons that exist. It focuses on the spike timing of a neuron and ignores the details of the action potential dynamics. These neurons are modeled as simple RC circuits. When the membrane potential is above a certain threshold, a spike is generated and the voltage is reset to its resting potential. This spike then signals other neurons through its synapses.

Neuronify aims to provide a low entry point to simulation-based neuroscience.

Difficulty level: Beginner
Duration: 01:25
Speaker: : Neuronify

Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.

This compilation is courtesy of freeCodeCamp.

Difficulty level: Beginner
Duration: 1:00:07
Speaker: : Shawn Grooms

This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.

This lesson was created by RootMath.

Difficulty level: Beginner
Duration: 1:21:30
Speaker: :

The state of the field regarding the diagnosis and treatment of major depressive disorder (MDD) is discussed. Current challenges and opportunities facing the research and clinical communities are outlined, including appropriate quantitative and qualitative analyses of the heterogeneity of biological, social, and psychiatric factors which may contribute to MDD.

Difficulty level: Beginner
Duration: 1:29:28