Manipulate the default connectome provided with TVB to see how structural lesions effect brain dynamics. In this hands-on session you will insert lesions into the connectome within the TVB graphical user interface. Afterwards the modified connectome will be used for simulations and the resulting activity will be analysed using functional connectivity.

This lecture focuses on where and how Jupyter notebooks can be used most effectively for education

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.

The practical usage of The Virtual brain in its graphical user interface and via python scripts is introduced. In the graphical user interface, you are guided through its data repository, simulator, phase plane exploration tool, connectivity editor, stimulus generator and the provided analyses. The implemented iPython notebooks of TVB are presented, and since they are public, can be used for further exploration of The Virtual brain.

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.

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

An overview of some of the essential concepts in neuropharmacology (e.g. receptor binding, agonism, antagonism), an introduction to pharmacodynamics and pharmacokinetics, and an overview of the drug discovery process relative to diseases of the Central Nervous System.

This talk highlights a set of platform technologies, software, and data collections that close and shorten the feedback cycle in research. 

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

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.