NeuroML 2 versions of BBP Neocortical Microcircuit Collaboration Portal cell models
These are the cell models used in the publication: Reconstruction and Simulation of Neocortical Microcircuitry, Markram et al. 2015, Cell, Volume 163, Issue 2, 456-492
Using the NeuroML 2 models
Install jNeuroML. Installation from source is recommended, using the latest development version, i.e.
git clone git://github.com/NeuroML/jNeuroML.git neuroml_dev/jNeuroML cd neuroml_dev/jNeuroML python getNeuroML.py development
jnml executable is present on your PATH.
Validating the NeuroML 2 files
To check validity of the NeuroML2 files use:
jnml -validate cNAC187_L1_HAC_f8c9772d9d_0_0.cell.nml
Convert cells and networks to graphical format
Image files of NeuroML 2 cells and networks can be generated in SVG format:
jnml cADpyr229_L23_PC_5ecbf9b163_0_0.cell.nml -svg
There is also a (less well developed) export to PNG format:
jnml cADpyr229_L23_PC_5ecbf9b163_0_0.cell.nml -png
Analyse channel properties
Information can be extracted from ion channels in neuroML2 format using pyNeuroML:
pynml-channelanalysis NaTa_t.channel.nml -erev 55 -stepTargetVoltage 10 -clampDuration 5 -i -duration 7 -clampDelay 1
Map models to NEURON format
jnml LEMS_L1_HAC_cNAC187_1.xml -neuron nrnivmodl nrngui LEMS_L1_HAC_cNAC187_1_nrn.py
Visualise the cell models with the OSB 3D Explorer
Cells and networks in valid NeuroML 2 can be visualised and analysed in the Open Source Brain 3D explorer. See here for an example:
The majority of the cell models in the BBP circuit are fully deterministic, but there are some (stuttering cells) which include stochastic ion channels, which introduces random fluctuations into the voltage traces. The NEURON mechanism for this channel (StochKv) is here.
A deterministic version of this ion channel is used in the NeuroML2 models. A comparison of the stochastic and deterministic mod files can be found here and a NeuroML2/LEMS version of the stochastic StochKv channel model is planned.