In this lesson you will learn about ion channels and the movement of ions across the cell membrane, one of the key mechanisms underlying neuronal communication. 

This lesson introduces the membrane potential equation

Explanation of the equivalent circuit model for a patch of passive neural membrane.

Solving the passive membrane equation

Injecting current into a passive membrane

Response to injected current

Explains the logic behind dealing with more complex currents by solving the membrane equation numerically.

Introducing voltage-dependent ion channels into the passive membrane

Introducing Hodgkin & Huxley's voltage dependent ion channel models, with emphasis on the sodium conductance

Introducing the classical Hodgkin & Huxley squid axon model with sodium and potassium conductances

This lesson extends the conductance-based model equation to multiple neuronal compartments, taking more complex morphology into account.

In this opening lesson, you will hear from the chair of the workshop (Neuroinformatics 2014 in Leiden, Netherlands), who gives an introduction and motivating argument underscoring the importance of collaboration in computational neuroscience.

This lesson gives an introduction to OpenWorm: an open-source project dedicated to creating a virtual C. elegans nematode in a computer.

The Open Source Brain (OSB) initiative (http://www.opensourcebrain.org) has been created to address the issues of poor accessibility, transparency, validation, and reuse of models in computational neuroscience.This lecture covers the aims of the Open Source Brain initiative, the current functionality of the website, and the range of models already available, and future plans for the project.

This lecture covers NeuronUnit, a library that builds upon SciUnit and integrates with several existing neuroinformatics resources to support validating single-neuron models using data gathered by neurophysiologists.

This lesson provides an introduction to the NeuroElectro project, which aims to organize information on cellular neurophysiology.

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.

The Virtual Brain (TVB) is an open-source, multi-scale, multi-modal brain simulation platform. In this lesson, you get introduced to brain simulation in general and to TVB in particular. This lesson also presents the newest approaches for clinical applications of TVB - that is, for stroke, epilepsy, brain tumors, and Alzheimer’s disease - and show how brain simulation can improve diagnostics, therapy, and understanding of neurological disease.

This lesson explains the mathematics of neural mass models and their integration to a coupled network. You will also learn about bifurcation analysis, an important technique in the understanding of non-linear systems and as a fundamental method in the design of brain simulations. Lastly, the application of the described mathematics is demonstrated in the exploration of brain stimulation regimes.

In this lesson, the simulation of a virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved clinical results. You will learn about the fundamentals of epilepsy, as well as the concepts underlying epilepsy simulation. By using an iPython notebook, the detailed process of this approach is explained step by step. In the end, you are able to perform simple epilepsy simulations your own.