Skip to main content

This lecture goes into detailed description of how to process workflows in the virtual research environment (VRE), including approaches for standardization, metadata, containerization, and constructing and maintaining scientific pipelines. 

Difficulty level: Intermediate
Duration: 1:03:55
Speaker: : Patrik Bey

This lesson provides an overview of how to conceptualize, design, implement, and maintain neuroscientific pipelines in via the cloud-based computational reproducibility platform Code Ocean. 

Difficulty level: Beginner
Duration: 17:01
Speaker: : David Feng

In this workshop talk, you will receive a tour of the Code Ocean ScienceOps Platform, a centralized cloud workspace for all teams. 

Difficulty level: Beginner
Duration: 10:24
Speaker: : Frank Zappulla

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: :

This video will document the process of creating a pipeline rule for batch processing on brainlife.

Difficulty level: Intermediate
Duration: 0:57
Speaker: :

This video will document the process of launching a Jupyter Notebook for group-level analyses directly from brainlife.

Difficulty level: Intermediate
Duration: 0:53
Speaker: :

This brief video walks you through the steps necessary when creating a project on brainlife.io. 

Difficulty level: Beginner
Duration: 1:45
Speaker: :

This brief video rus through how to make an accout on brainlife.io.

Difficulty level: Beginner
Duration: 0:30
Speaker: :

This video will document how to run a correlation analysis between the gray matter volume of two different structures using the output from brainlife app-freesurfer-stats.

Difficulty level: Beginner
Duration: 1:33
Speaker: :

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.

Difficulty level: Intermediate
Duration: 3:09:12

As a part of NeuroHackademy 2020, this lecture delves into cloud computing, focusing on Amazon Web Services. 

Difficulty level: Beginner
Duration: 01:43:59

This talk presents an overview of CBRAIN, a web-based platform that allows neuroscientists to perform computationally intensive data analyses by connecting them to high-performance computing facilities across Canada and around the world.

Difficulty level: Beginner
Duration: 56:07
Speaker: : Shawn Brown

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

 

This lesson corresponds to slides 65-90 of the PDF below. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

JupyterHub is a simple, highly extensible, multi-user system for managing per-user Jupyter Notebook servers, designed for research groups or classes. This lecture covers deploying JupyterHub on a single server, as well as deploying with Docker using GitHub for authentication.

Difficulty level: Beginner
Duration: 1:36:27
Speaker: : Thomas Kluyver

This demonstration walks through how to import your data into MATLAB.

Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®