Difficulty level

This talk introduces Bayes' theorem, which describes the probability of an event, based on prior knowledge of conditions that might be related to the event.

Difficulty level: Beginner
Duration: 7:57
Speaker: : Barton Poulson

This lesson recaps why math, in a number of ways, is extremely useful in data science.

Difficulty level: Beginner
Duration: 1:35
Speaker: : Barton Poulson

This lesson provides an introduction to the lessons in this course that deal with statistics and why they are useful for data science.

Difficulty level: Beginner
Duration: 4:01
Speaker: : Barton Poulson

In this lesson, users will learn about the importance of exploratory analysis, as well as how statistics enables one to become familiar with and understand one's data.

Difficulty level: Beginner
Duration: 2:23
Speaker: : Barton Poulson

This lesson goes over graphical data exploration, including motivations for its use as well as practical examples of visualizing data distributions.

Difficulty level: Beginner
Duration: 8:01
Speaker: : Barton Poulson

In this lesson, users learn about exploratory statistics, and are introduced to various methods for numerical data exploration.

Difficulty level: Beginner
Duration: 5:05
Speaker: : Barton Poulson

This lesson overview some simple descriptions of statistical data.

Difficulty level: Beginner
Duration: 10:16
Speaker: : Barton Poulson

This lesson covers the basics of hypothesis testing.

Difficulty level: Beginner
Duration: 6:04
Speaker: : Barton Poulson

In this lecture, the speaker demonstrates Neurokernel's module interfacing feature by using it to integrate independently developed models of olfactory and vision LPUs based upon experimentally obtained connectivity information.

Difficulty level: Intermediate
Duration: 29:56
Speaker: : Aurel A. Lazar

This lesson describes the Neuroscience Gateway , which facilitates access and use of National Science Foundation High Performance Computing resources by neuroscientists.

Difficulty level: Beginner
Duration: 39:27
Speaker: : Subha Sivagnanam

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.

Difficulty level: Beginner
Duration: 02:49:34

This lesson provides a short overview of the main features of the Canadian Open Neuroscience Platform (CONP) Portal, 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.

Difficulty level: Beginner
Duration: 14:03

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.

Difficulty level: Beginner
Duration: 56:07
Speaker: : Shawn Brown

In this talk the speakers will give a brief introduction of the Fenix Infrastructure and Service Offering, before focusing on Data Safety. The speaker will take the participants through the ETHZ-CSCS offering for EBRAINS and all the HBP Communities highlighting the Infrastructure role in a service implementation in respect of Security. Particular attention will be on showing what tools ETHZ-CSCS provides to a Portal/Service provider such as EBRAINS, MIP/HIP, TVB, NRP amongst others. Finally there will be given a quick glimpse into the future and the role that “multi-tenancy” will play.

Difficulty level: Intermediate
Duration: 20:05

This lesson is a general overview of overarching concepts in neuroinformatics research, with a particular focus on clinical approaches to defining, measuring, studying, diagnosing, and treating various brain disorders. Also described are the complex, multi-level nature of brain disorders and the data associated with them, from genes and individual cells up to cortical microcircuits and whole-brain network dynamics. Given the heterogeneity of brain disorders and their underlying mechanisms, this lesson lays out a case for multiscale neuroscience data integration.

Difficulty level: Intermediate
Duration: 1:09:33
Speaker: : Sean Hill

In this tutorial on simulating whole-brain activity using Python, participants can follow along using corresponding code and repositories, learning the basics of neural oscillatory dynamics, evoked responses and EEG signals, ultimately leading to the design of a network model of whole-brain anatomical connectivity.

Difficulty level: Intermediate
Duration: 1:16:10
Speaker: : John Griffiths

This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment.

This lesson corresponds to slides 1-64 in the PDF below.

Difficulty level: Intermediate
Duration: 1:28:14

This talk gives a brief overview of current efforts to collect and share the Brain Reference Architecture (BRA) data involved in the construction of a whole-brain architecture that assigns functions to major brain organs.

Difficulty level: Beginner
Duration: 4:02

This brief talk discusses the idea that music, as a naturalistic stimulus, offers a window into higher cognition and various levels of neural architecture.

Difficulty level: Beginner
Duration: 4:04
Speaker: : Sarah Faber

In this short talk you will learn about The Neural System Laboratory, which aims to develop and implement new technologies for analysis of brain architecture, connectivity, and brain-wide gene and molecular level organization.

Difficulty level: Beginner
Duration: 8:38
Speaker: : Trygve Leergard