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.

In this lesson you will learn about the ionic basis of the action potential, including the Hodgkin-Huxley model. 

This lesson provides an overview of plasticity on many levels, including short-term, long-term, metaplasticity, and structural plasticity. The lesson also provides xamples related to modelling of biochemical networks. 

Note: The sound uptake is a bit noisy the first few minutes, but gets better from about 5 mins in

This lesson gives an introduction to the modelling of chemical computation in the brain.

In this lesson you will hear about several computationally demanding studies of synaptic plasticity on the molecular level.

This lesson provides an introduction to the role of models in theoretical neuroscience.

This lesson introduces different types of models, model complexity, and how to choose an appropriate model.

This lesson gives an overview of balanced excitatory-inhibitory (E-I) networks, stability, and gain modulation.

In this lesson, you will learn about methods for dimensionality reduction of data, with a focus on factor analysis.

This lesson gives an in-depth look into various types of neuronal networks, as well properties, parameters, and phenomena which characterize them.