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Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (antibodies, model organisms and software projects) in the biomedical literature to improve transparency of research methods.

Difficulty level: Beginner
Duration: 1:01:36
Speaker: : Maryann Martone

Introduction to the Brain Imaging Data Structure (BIDS): a standard for organizing human neuroimaging datasets. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 56:49

This lecture and tutorial focuses on measuring human functional brain networks. The lecture and tutorial were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 50:44
Speaker: : Caterina Gratton
Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®
Difficulty level: Beginner
Duration: 15:10
Speaker: : MATLAB®
Difficulty level: Beginner
Duration: 2:49
Speaker: : MATLAB®
Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®

This tutorial illustrates several ways to approach predictive modeling and machine learning with MATLAB.

Difficulty level: Beginner
Duration: 6:27
Speaker: : MATLAB®
Difficulty level: Beginner
Duration: 3:55
Speaker: : MATLAB®
Difficulty level: Beginner
Duration: 3:52
Speaker: : MATLAB®

A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni

This tutorial was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 1:26:02
Speaker: : Ariel Rokem

This tutorial was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 1:21:40
Speaker: : Tal Yarkoni
Course:

Agah Karakuzu takes a spaghetti script written in MATLAB and turns it into understandable and reusable code living happily in a powerful GitHub repository.

Difficulty level: Beginner
Duration: 02:08:19
Speaker: :
Course:

Basic knowledge and comfort with Command Line Interfaces (CLI) is highly beneficial for learning how to use countless neuroscience tools and acquiring programming skills.  Furthermore, CLIs are better disposed to reproducibility, automation, concatenation in pipelines, execution on multiple platforms, and remote access.

 

Ross Markello takes you through this general introduction to the essentials of navigating through a Bash terminal environment.  The lesson is based on the Software Carpentries "Introduction to the Shell" and was given in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 01:12:22
Speaker: :
Course:

Ross Markello provides an overview of Python applications to data analysis, demonstrating why it has become ubiquitous in data science and neuroscience.

 

The lesson was given in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 02:38:45
Speaker: :

Introduction to the central concepts of machine learning, and how they can be applied in Python using the Scikit-learn Package. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 2:22:28
Speaker: : Jake Vanderplas

Much like neuroinformatics, data science uses techniques from computational science to derive meaningful results from large complex datasets. In this session, we will explore the relationship between neuroinformatics and data science, by emphasizing a range of data science approaches and activities, ranging from the development and application of statistical methods, through the establishment of communities and platforms, and through the implementation of open-source software tools. Rather than rigid distinctions, in the data science of neuroinformatics, these activities and approaches intersect and interact in dynamic ways. Together with a panel of cutting-edge neuro-data-scientist speakers, we will explore these dynamics

 

This lecture covers self-supervision as it relates to neural data tasks and the Mine Your Own vieW (MYOW) approach.

Difficulty level: Beginner
Duration: 25:50
Speaker: : Eva Dyer

Estefany Suárez provides a conceptual overview of the rudiments of machine learning, including its bases in traditional statistics and the types of questions it might be applied to.

 

The lesson was presented in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 01:22:18
Speaker: :

Jake Vogel gives a hands-on, Jupyter-notebook-based tutorial to apply machine learning in Python to brain-imaging data.

 

The lesson was presented in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 02:13:53
Speaker: :