In this lesson you will 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.
This short video walks you through the steps of publishing a dataset on brainlife, an open-source, free and secure reproducible neuroscience analysis platform.
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).
This video will document the process of running an app on brainlife, from data staging to archiving of the final data outputs.
This video will document the process of visualizing the provenance of each step performed to generate a data object on brainlife.
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.
This brief video walks you through the steps necessary when creating a project on brainlife.io.
This brief video rus through how to make an accout on brainlife.io.
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.
As a part of NeuroHackademy 2020, this lecture delves into cloud computing, focusing on Amazon Web Services.
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.
This hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines.
This video will document the process of uploading data into a brainlife project using ezBIDS.
This quick video presents some of the various visualizers available on brainlife.io
This lesson consists of a demonstration of the BRIAN Simulator. BRIAN is a free, open-source simulator for spiking neural networks. It is written in the Python programming language and is available on almost all platforms, and is designed to be easy to learn and use, highly flexible, and easily extensible.
This lesson provides a demonstration of NeuroFedora, a volunteer-driven initiative to provide a ready-to-use Fedora-based free and open-source software platform for neuroscience. By making the tools used in the scientific process easier to use, NeuroFedora aims to aid reproducibility, data sharing, and collaboration in the research community.The CompNeuro Fedora Lab was specially to enable computational neuroscience.
This lesson provides an introduction and live demonstration of neurolib, a computational framework for simulating coupled neural mass models written in Python. Neurolib provides a simulation and optimization framework which allows you to easily implement your own neural mass model, simulate fMRI BOLD activity, analyse the results and fit your model to empirical data.
In this lesson, you will learn about the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks. GeNN is an open-source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users.
This video gives a short introduction to the EBRAINS data sharing platform, why it was developed, and how it contributes to open data sharing.
This video demonstrates how to find, access, and download data on EBRAINS.