Tutorials & E-Library

These tutorials show how to use the CellBuilder, a powerful and convenient tool for constructing and managing models of individual neurons. The CellBuilder is a "graphical form for specifying the properties of a model cell." It breaks the job of model specification into a sequence of tasks :

Setting up model topology (branching pattern).
Grouping sections with shared properties into subsets.
Assigning geometric properties (length, diameter) to subsets or individual sections, and specifying a discretization strategy (i.e. how to set nseg).
Assigning biophysical properties (Ra, cm, ion channels, buffers, pumps, etc.) to subsets or individual sections.

These are the same things we would have to do, and pretty much the same sequence we'd follow, in order to define a model by writing hoc code. However, the CellBuilder helps us keep it all nice and organized, and eliminates a lot of error-prone typging.

This outline is based on a talk at the course "Using the NEURON Simulation Environment" that was presented on Oct. 25, 1997 at the 27th Annual Meeting of the Society for Neuroscience in New Orleans, LA. It will help you get started creating models and managing them with the graphical user interface.

This tutorial will showcase how you can access SpiNNaker and use it through the Jupiter Lab Interface. Furthemore, we will be looking into installation of libraries, terminal access, specifying neurons and recording spikes. Finally you will get an introduction to delays, random weights and stdp spike timing dependent plasticity.

Andrew Rowley is showcasing the many sides of SpiNNaker in this Infrastructure Training Tutorial.

Lear how to use the SpiNNaker neuromorphic compute system interactively.

This presentation will introduce you to the SpiNNaker neuromorphic compute system, touching upon its development and what it can do and for what it can be used.

Brief introduction to the SpiNNaker and BrainScaleS neuromorphic compute systems given by Steve Furber on 15 October 2021 during the Neuromorphic computing breakout session at the Human Brain Project Summit 2021.

MUSIC has recently acquired a plain Python interface to go along with the C++ API. If you just want to connect with a simulation rather than adding MUSIC capability to a simulator, this Python interface can be a lot more convenient than C++. You have Numpy, Scipy and other high-level libraries available, and you don’t need to compile anything.

SLI is the built-in scripting language in NEST. It is a stack-based language loosely modelled on PostScript. It is quite cumbersome to work with, is not extensively documented, and has quite a few corner cases, design issues and unintended behaviours. But it is small, already built into NEST and is much more memory efficient than using Python. If your models are very large and memory is tight, or you are using a system where Python isn’t available, then SLI is the way to go.

The C++ interface is the lowest-level interface and what you would use to implement a MUSIC interface in simulators. But it is not a complicated API, so you can easily use it for your own applications that connect to a MUSIC-enabled simulation.

An example of two NEST simulations connected through MUSIC.