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.
This lesson recaps why math, in a number of ways, is extremely useful in data science.
This lesson provides an introduction to the lessons in this course that deal with statistics and why they are useful for data science.
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.
This lesson goes over graphical data exploration, including motivations for its use as well as practical examples of visualizing data distributions.
In this lesson, users learn about exploratory statistics, and are introduced to various methods for numerical data exploration.
This lesson overview some simple descriptions of statistical data.
This lesson covers the basics of hypothesis testing.
This lesson describes the Neuroscience Gateway , which facilitates access and use of National Science Foundation High Performance Computing resources by neuroscientists.
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 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.
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.
How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.
This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.
This lesson covers the ionic basis of the action potential, including the Hodgkin-Huxley model.
This lesson provides an introduction to the myriad forms of cellular mechanisms whicn underpin healthy brain function and communication.
In this lesson you will learn about the ionic basis of the action potential, including the Hodgkin-Huxley model.
This lesson provides an introduction to the course Cellular Mechanisms of Brain Function.
This lesson covers membrane potential of neurons, and how parameters around this potential have direct consequences on cellular communication at both the individual and population level.
This lesson covers the spatiotemporal dynamics of the membrane potential.