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

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 lecture focuses on how the immune system can target and attack the nervous system to produce autoimmune responses that may result in diseases such as multiple sclerosis, neuromyelitis, and lupus cerebritis manifested by motor, sensory, and cognitive impairments. Despite the fact that the brain is an immune-privileged site, autoreactive lymphocytes producing proinflammatory cytokines can cause active brain inflammation, leading to myelin and axonal loss.

This lecture will provide an overview of neuroimaging techniques and their clinical applications.

This lecture picks up from the previous lesson, providing an overview of neuroimaging techniques and their clinical applications.

This lesson discusses both state-of-the-art detection and prevention schema in working with neurodegenerative diseases. 

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

In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.

This lecture focuses on the rationale for employing neuroimaging methods for movement disorders.

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

In this lesson, you will learn about the current challenges facing the integration of machine learning and neuroscience. 

This demonstration walks through how to import your data into MATLAB.

This lesson provides instruction regarding the various factors one must consider when preprocessing data, preparing it for statistical exploration and analyses. 

This tutorial outlines, step by step, how to perform analysis by group and how to do change-point detection.

This tutorial walks through several common methods for visualizing your data in different ways depending on your data type.

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