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.
The Canadian Open Neuroscience Platform (CONP) Portal is a web interface that facilitates open science for the neuroscience community by simplifying global access to and sharing of datasets and tools. The Portal internalizes the typical cycle of a research project, beginning with data acquisition, followed by data processing with published tools, and ultimately the publication of results with a link to the original dataset.
In this video, Samir Das and Tristan Glatard give a short overview of the main features of the CONP Portal.
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.
This course will teach you AWS basics right through to advanced cloud computing concepts. There are lots of hands-on exercises using an AWS free tier account to give you practical experience with Amazon Web Services. Visual slides and animations will help you gain a deep understanding of Cloud Computing.
This lesson is courtesy of freeCodeCamp.
As models in neuroscience have become increasingly complex, it has become more difficult to share all aspects of models and model analysis, hindering model accessibility and reproducibility. In this session, we will discuss existing resources for promoting FAIR data and models in computational neuroscience, their impact on the field, and the remaining barriers. This lecture covers how FAIR practices affect personalized data models, including workflows, challenges, and how to improve these practices.
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 how brainlife.io works, and how it can be applied to neuroscience data.
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.
Learn how to build and share extensions in NWB
Learn how to build custom APIs for extension
Learn how to handle writing very large data in PyNWB
Learn how to handle writing very large data in MatNWB
This video explains what metadata is, why it is important, and how you can organise your metadata to increase the FAIRness of your data on EBRAINS.
Elizabeth Dupre provides reviews some standards for project management and organization, including motivation in the view of the FAIR principles and improved reproducibility.
This module explores sensation in the brain: what organs are involved, sensory pathways, processing centers, and theories of integration. We cover sensory transduction, vision, audition olfaction, gustation, and somatosensation.
This module covers how the brain interacts with the world through motor movements. Motor movements underlie so much of our functioning, our speech, the opening and closing of our eyes, and the beating of our hearts. We’ll learn about areas of the brain involved in movement and some of its pathways.
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.