Learn how to simulate seizure events and epilepsy in The Virtual Brain. We will look at the paper: On the Nature of Seizure Dynamics which describes a new local model called the Epileptor, and apply this same model in The Virtual Brain. This is part 1 of 2 in a series explaining how to use the Epileptor. In this part, we focus on setting up the parameters.

As a part of NeuroHackademy 2020, Tara Madhyastha (University of Washington), Andrew Crabb (AWS), and Ariel Rokem (University of Washington) give a lecture on Cloud Computing, focusing on Amazon Web Services. 

This video is provided by the University of Washington eScience Institute.

Shawn Brown 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.

This talk was given in the context of a Ludmer Centre event in 2019.

Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience.  FAIR defines a set of high-level principles and practices for making digital objects, including data, software, and workflows, Findable, Accessible,  Interoperable, and Reusable.  But FAIR is not a specification;  it leaves many of the specifics up to individual scientific disciplines to define.  INCF has been leading the way in promoting, defining, and implementing FAIR data practices for neuroscience.  We have been bringing together researchers, infrastructure providers, industry, and publishers through our programs and networks.  In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience.  We will engage in a discussion on questions such as:  how is neuroscience doing with respect to FAIR?  What have been the successes?  What is currently very difficult? Where does neuroscience need to go?

This lecture covers FAIR atlases, from their background, their construction, and how they can be created in line with the FAIR principles.

This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

EyeWire is a game to map the brain. Players are challenged to map branches of a neuron from one side of a cube to the other in a 3D puzzle. Players scroll through the cube and reconstruct neurons with the help of an artificial intelligence algorithm developed at Seung Lab in Princeton University. EyeWire gameplay advances neuroscience by helping researchers discover how neurons connect to process visual information. 

Mozak is a scientific discovery game about neuroscience for citizen scientists and neuroscientists alike. Players to help neuroscientists build models of brain cells and learn more about the brain through their efforts.

This module explains how neurons come together to create the networks that give rise to our thoughts. The totality of our neurons and their connection is called our connectome. Learn how this connectome changes as we learn, and computes information. We will also learn about physiological phenomena of the brain such as synchronicity that gives rise to brain waves.

This lecture provides an introduction to the study of eye-tracking in humans. 

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

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.

This lecture covers the description and brief history of data science and its use in neuroinformatics.