"Increasingly, the real limit on what computational scientists can accomplish is how quickly and reliably they can translate their ideas into working code."
Gregory V. Wilson, Where's the Real Bottleneck in Scientific Computing?
"programming the complexity telescope for brain-like computing"
News
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3rd INCF Congress of Neuroinformatics
[more]
February 4th, 2010 -
NE.O welcomes The Brian Simulator
[more]
January 10th, 2010 -
Slides from FACETS CodeJam #3
[more]
November 3rd, 2009 -
FACETS CodeJam #3 Registration deadline approaching
[more]
September 3rd, 2009 -
CodeNode - interactive online programming notebook
[more]
September 2nd, 2009 -
NE.O Job Listings
[more]
August 11th, 2009 -
PyNN 0.5.0 released
[more]
June 9th, 2009 -
EuroScipy 2009 in Leipzig, Germany
[more]
April 30th, 2009 -
CNS workshop “Python in Neuroscience”: call for participation
[more]
April 1st, 2009 -
Advanced Scientific Programming in Python G-Node Summer School
[more]
March 26th, 2009 -
2nd INCF Congress of Neuroinformatics
[more]
February 23rd, 2009 -
When will NumPy and SciPy move to Python 3.0?
[more]
February 5th, 2009 -
Hot off the press: PyNN, PyNEST, NEURON+Python, Brian
[more]
January 6th, 2009 -
Python 3.0 final released
[more]
December 4th, 2008 -
NeuroTools 0.1 (Asynchronous Astrocyte) released
[more]
November 13th, 2008 -
NeuroTools Live Demo @ INCF Booth, SfN 2008. (Nov 16; 9:30-12:30)
[more]
November 12th, 2008 -
BCCN/FACETS Student Workshop: Using Python for Computational Neuroscience
[more]
June 13th, 2008 -
PyNN 0.4.1 released
[more]
June 12th, 2008 -
Cookbook launched
[more]
June 9th, 2008 -
Call for Contributions - Python in Neuroscience Special Section
[more]
June 3rd, 2008
About
Trends in programming language development and adoption point to Python as the high-level systems integration language of choice. Python leverages a vast developer-base external to the Neuroscience community, and promises leaps in simulation complexity and maintainability to any neural simulator which adopts it. As more and more simulators support Python, model development times can be drastically reduced by promoting code sharing and reuse across simulator communities. As a result, modellers can devote their software development time to innovating new simulation tools such as network topology databases, stimulus programming, analysis and visualisation tools, and simulation accounting, to name a few.
- NeuralEnsemble
- is a multilateral effort to coordinate and organise Neuroscience software development efforts into a larger meta-simulator software system, a natural and alternate approach to incrementally address what is known as the complexity bottleneck, presently a major roadblock for neural modelling. While a solution here is arguably a necessary condition for resolving the present stalemate for understanding the complexities of brain-like computing, a successful initiative could also end up being a major innovation of the field for the larger computing community.
Community
There is a NeuralEnsemble Google group for discussion of collaborative neuroscience software development in Python and to provide software support. If you have any questions about any of the software listed below, please join the group and post a message in one of the forums.
Software
NeuralEnsemble hosts Trac/Subversion servers for a number of open-source neuroscience tools:
- The Brian Simulator
- Brian is a simulator for spiking neural networks available on almost all platforms. The motivation for this project is that a simulator should not only save the time of processors, but also the time of scientists. Brian is easy to learn and use, highly flexible and easily extensible. The Brian package itself and simulations using it are all written in the Python programming language.
- NeuroTools
- a set of tools written in Python to manage, store and analyse computational neuroscience simulations.
- OpenElectrophy
- OpenElectrophy is a tool written in Python and based on a MySQL database for organising, computing, and visualising neural data from intra- and extra-cellular recording. It can be used, for example, both for studying spike and local field oscillations.
- PyNN
- a Python package for simulator-independent specification of neuronal network models. In other words, you can write the code for a model once, using the PyNN API, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST, Brian and PCSIM).
Last updated 11.01.2010. Contact: admin at neuralensemble dot org.