News
-
Python 3.0 final released
[more]
Thu, 04 Dec 2008 12:11:00 +0100
-
NeuroTools 0.1 (Asynchronous Astrocyte) released
[more]
Thu, 13 Nov 2008 14:16:00 +0100
-
NeuroTools Live Demo @ INCF Booth, SfN 2008. (Nov 16; 9:30-12:30)
[more]
Wed, 12 Nov 2008 10:53:00 +0100
-
BCCN/FACETS Student Workshop: Using Python for Computational Neuroscience
[more]
Fri, 13 Jun 2008 18:53:00 +0200
-
PyNN 0.4.1 released
[more]
Thu, 12 Jun 2008 13:39:00 +0200
-
Cookbook launched
[more]
Mon, 09 Jun 2008 18:44:00 +0200
-
Call for Contributions - Python in Neuroscience Special Section
[more]
Tue, 03 Jun 2008 13:41:00 +0200
Abstract
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:
- 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 and PCSIM).
- NeuroTools
- a set of tools written in Python to manage, store and analyse computational neuroscience simulations.
- nrnpy
- an experimental branch of the NEURON code-base, focused on improving and extending the integration of the Python programming language into NEURON.
- FacetsML
- FACETS extensions to NeuroML towards declarative specification of large-scale network 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.
Notes:
- Anonymous read access is granted to all.
- Write access requires an account. FACETS members can use their FACETS forum account.
- Everybody else needs to contact Eilif for a password.
- Automated registration pages and the ability to invite colleagues are planned features.
- Please contact Eilif if you would like a trac+svn for your project.
Meetings
Some coding highlights of the meeting:
- As of the CodeJam, PyNN now supports NEURON, NEST, PCSIM, and FACETS Stage1 hardware back-ends.
- PyNN, nrnpy, NeuroTools trac+svn are running on the neuralensemble server.
- Preliminary glue code binding Laurent Perrinet's retina model into James Bednar's Topographica was achieved.
- Array types were added to NEST 2.0 providing a clean remedy to the PythonDatum hack to exchange numpy arrays between Python and NEST/SLI.
- pynest 2.0 was added as a standard feature to NEST 2.0 and the build processes unified.
- nrnpy, the Python enabled NEURON: support for getting and setting numpy arrays, progress making HOC objects first class python objects.
Concrete outstanding issues for future CodeJams:
- No time was found to look at distributed simulation + PyNN.
- PyNN back-ends for MVASpike, NeuroML.
- PyNN: direct writes of simulation output hdf5 in a standard way, supporting distributed/multithread PyNN.
- Concrete solutions to package management.