Arbor and NeuroML

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Arbor is a high performance multicompartmental neural simulation library. Addition of support for NeuroML2 and LEMS is under active development.

Importing NeuroML into Arbor

The current approach to supporting NeuroML in Arbor involves importing NeuroML to Arbor’s internal format.

See here for Arbor’s own documentation on this. It involves calling the neuroml() method in arbor pointing at the NeuroML file containing the cell you wish to load:

nml = arbor.neuroml('mymorphology.cell.nml')

See here for a worked example of this, importing a multicompartmental cell with only a passive membrane conductance.

Support for channels/synapses in LEMS

There is work under way to allow reading of the dynamics of ion channels and synapses which are specified in LEMS into Arbor.

See https://github.com/thorstenhater/nmlcc for more details.

Network models in Arbor with NeuroMLlite

There is preliminary support for building network specified in NeuroMLlite format directly in Arbor. See here for an example.

Examples

Example code for interactions between NeuroML models and Arbor can be found in the Arbor Showcase repository.