PyNN and NeuroML
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PyNN and NeuroML are independently developed approaches to allow portability of models across simulators. These reflect 2 differing approaches to model specification:

  • Declarative specification: the structure of the model is explicitly specified in a structured model exchange format. XML is well suited as a basis for a language in this format, and is used by NeuroML as well as SBML and CellML.
  • Procedural specification: the function calls or procedures for building a model are standardised. This is the case with PyNN, where Python scripts can be used to create simulations on multiple simulators.

These approaches are complementary, and a number of options are available to allow interaction between PyNN and model components in NeuroML (in particular NeuroML v2.0).


Information on the latest developments towards greater interaction between PyNN & NeuroML2 can be found here here and examples of the conversions can be found on Open Source Brain.


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