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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

Tutorial on collaborating with Git and GitHub. This tutorial was 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: 2:15:50
Speaker: : Elizabeth DuPre
Course:

Colt Steele provides a comprehensive introduction to the command line and 50 popular Linux commands.  This is a long course (nearly 5 hours) but well worth it if you are going to spend a good part of your career working from a terminal, which is likely if you are interested in flexibility, power, and reproducibility in neuroscience research.

 

This lesson is courtesy of freeCodeCamp.

Difficulty level: Beginner
Duration: 05:00:16
Speaker: :

Félix-Antoine Fortin from Calcul Québec gives an introduction to high-performance computing with the Compute Canada network, first providing an overview of use cases for HPC and then a hand-on tutorial.  Though some examples might seem specific to the Calcul Québec, all computing clusters in the Compute Canada network share the same software modules and environments.

 

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

Difficulty level: Beginner
Duration: 02:49:34
Speaker: :

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

Lecture on functional brain parcellations and a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation which 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: Advanced
Duration: 50:28
Speaker: : Pierre Bellec

Learn how to handle writing very large data in MatNWB

Difficulty level: Advanced
Duration: 16:18
Speaker: : Ben Dichter

Overview of the CaImAn package, and demonstration of usage with NWB

Difficulty level: Intermediate
Duration: 44:37

Overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters

Difficulty level: Intermediate
Duration: 1:10:28
Speaker: : Alessio Buccino

Overview of the NWBWidgets package, including coverage of different data types, and information for building custom widgets within this framework

Difficulty level: Intermediate
Duration: 47:15
Speaker: : Ben Dichter

Elizabeth Dupre provides reviews some standards for project management and organization, including motivation in the view of the FAIR principles and improved reproducibility.

Difficulty level: Beginner
Duration: 01:08:34
Speaker: : Elizabeth DuPre

Tutorial on how to simulate brain tumor brains with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls. Authors: Hannelore Aerts, Michael Schirner, Ben Jeurissen, DIrk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo

Difficulty level: Intermediate
Duration: 10:01
Speaker: :

Peer Herholz gives a tour of how popular virtualization tools like Docker and Singularity are playing a crucial role in improving reproducibility and enabling high-performance computing in neuroscience.

Difficulty level: Beginner
Duration:
Speaker: :

How genetics can contribute to our understanding of psychiatric phenotypes.

Difficulty level: Beginner
Duration: 55:15
Speaker: : Sven Cichon

The landscape of scientific research is changing. Today’s researchers need to participate in large-scale collaborations, obtain and manage funding, share data, publish, and undertake knowledge translation activities in order to be successful. As per these increasing demands, Science Management is now a vital piece of the environment.

Difficulty level: Beginner
Duration: 18:13
Speaker: : Mojib Javadi

Introduction to reproducible research. The lecture provides an overview of the core skills and practical solutions required to practice reproducible research. 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: 1:25:17
Speaker: : Fernando Perez

The FOSTER portal has produced a number of guides to help implement Open Science practices in daily workflows, including The Open Science Training Handbook.  It provides many basic definitions, concepts, and principles that are key components of open science, as well as general guidance for developing and implementing these practices in one's own research environments.

 

Topics include:

  • Open Concepts and Principles
  • Open Research Data and Materials
  • Open Research Software and Open Source
  • Reproducible Research and Data Analysis
  • Open Access to Published Research Results
  • Open Licensing and File Formats
  • Collaborative Platforms
  • Open Peer Review, Metrics and Evaluation
  • Open Science Policies
  • Citizen Science
  • Open Educational Resources
  • Open Advocacy
Difficulty level: Beginner
Duration:
Speaker: :