This lesson gives an introduction to high-performance computing with the Compute Canada network, first providing an overview of use cases for HPC and then a hands-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.
This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.
This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.
This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.
This lecture contains an overview of electrophysiology data reuse within the EBRAINS ecosystem.
In this lesson, while learning about the need for increased large-scale collaborative science that is transparent in nature, users also are given a tutorial on using Synapse for facilitating reusable and reproducible research.
The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.
This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community.
This lecture provides an overview of The Virtual Brain Simulation Platform.
This lesson gives a description of the BrainHealth Databank, a repository of many types of health-related data, whose aim is to accelerate research, improve care, and to help better understand and diagnose mental illness, as well as develop new treatments and prevention strategies.
This lesson corresponds to slides 46-78 of the PDF below.
This lesson describes not only the need for precision medicine, but also the current state of the methods, pharmacogenetic approaches, utility and implementation of such care today.
This lesson corresponds to slides 1-50 of the PowerPoint below.
This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.
This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.
This lecture focuses on the structured validation process within computational neuroscience, including the tools, services, and methods involved in simulation and analysis.
This session provides users with an introduction to tools and resources that facilitate the implementation of FAIR in their research.
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.
The state of the field regarding the diagnosis and treatment of major depressive disorder (MDD) is discussed. Current challenges and opportunities facing the research and clinical communities are outlined, including appropriate quantitative and qualitative analyses of the heterogeneity of biological, social, and psychiatric factors which may contribute to MDD.
This lesson delves into the opportunities and challenges of telepsychiatry. While novel digital approaches to clinical research and care have the potential to improve and accelerate patient outcomes, researchers and care providers must consider new population factors, such as digital disparity.
This lesson provides a basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.
This lecture gives an introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.