Porting a model from NEURON to PyNN: a case study
Managing complex workflows in neural simulation/data analysis
Workflows for reproducible research in comp. neurosci.
Modelling simple neurons with PyMOOSE
From Hoc to Python: a case study
Accessing hoc from Python
Modelling single cells in NEURON with the Python interpreter
Installation of NEURON with Python
Modelling STDP in the NEURON simulator
- An initiative to foster collaborative software development and good software development practices
in neuroscience, with an emphasis on use of the Python programming language.
Includes hosting for open-source neuroscience software, the
NeuralEnsemble Google Group, and the
- a Python package for simulator-independent specification of spiking 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. more ...
- Automated tracking of numerical experiments, for reproducible research.
- The goal of Neo is to improve interoperability between Python tools for working with
electrophysiology data, by providing a common, shared object model and support for reading a wide range of
neurophysiology file formats. more ...
- NeuroML and NineML
- NeuroML and NineML are XML-based languages for describing neuronal network models. I am currently involved in
developing associated Python libraries: see
libNeuroML and the
NineML Python API.
- Python tools to simplify the life of a computational neuroscientist, including simulation setup and
instrumentation, data storage, analysis and visualisation.
- A framework to make it easier for neuroscientists to build a customised database for their experimental data.