This lesson introduces methods for dimensionality reduction of data, with focus on factor analysis.

This lecture delves into the dynamics of neural computation, from the spiking activity of single neurons to regional cortical population coding and network activity.

This lesson provides an overview on spiking neuron networks and linear response models.

In this lesson, you will learn about Bayesian neuron models and parameter estimation.

This lecture describes Bayesian memory and learning; how to go from observations to latent variables.

This lesson introduces the concept of constraints on information processing, and how studying these constraints can reveal valuable knowledge about how the brain and other systems function. 

This lecture discusses approaching neural systems from an evolutionary perspective.

This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.

This lesson provides a short reel on who we are, what we're doing and why we're doing it.

This video will teach you the basics of navigating the Open Science Framework and creating your first projects.

This webinar walks you through the basics of creating an OSF project, structuring it to fit your research needs, adding collaborators, and tying your favorite online tools into your project structure.

This webinar will introduce how to use the Open Science Framework (OSF) in a classroom setting.

This lesson provides instruction on how to organize related projects with OSF features such as links, forks, and templates.

This webinar will introduce the integration of JASP Statistical Software with the Open Science Framework (OSF).

This lesson describes the value of version control, as well as how to do so with your own files and data on OSF. 

This lecture focuses on where and how Jupyter notebooks can be used most effectively for education.

JupyterHub is a simple, highly extensible, multi-user system for managing per-user Jupyter Notebook servers, designed for research groups or classes. This lecture covers deploying JupyterHub on a single server, as well as deploying with Docker using GitHub for authentication.

This lecture provides an introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.

This lesson provides an introduction to simple spiking neuron models.