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NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail

Figure 9

Comparison of the behavior of NeuroML-based cortical and thalamic cell models run on NEURON, GENESIS and MOOSE simulators.

(A) Single compartment cell model containing all 22 active conductances present in the detailed cell models (Supporting Table S2), together with a passive conductance and a decaying calcium pool. Left plot shows the membrane potential response to a 80 pA current injection on NEURON (black), GENESIS (red) and MOOSE (green). Right plot shows the behavior on NEURON of the activation variables for the anomalous rectifier (thick black line), L-type Ca2+ (red) and persistent Na+ conductances (green) and the inactivation variable of the fast Na+ conductance (blue). White curve overlays show the corresponding GENESIS traces, and dashed lines show MOOSE traces. (B–E) 3D representations of four cell models from Traub et al. [15] implemented in NeuroML, color indicates the density of fast sodium conductances on the cell membrane (red: high - yellow: low). Graphs show somatic membrane potential during current injections for: (B) regular spiking (RS) Layer 2/3 pyramidal cell; (C) superficial low threshold spiking (LTS) interneuron; (D) intrinsically bursting (IB) Layer 5 pyramidal cell; (E) nucleus reticularis thalami (nRT) cell (trace colors as for left panel of A). See Supporting Figure S3 for further details of these and the 6 other electrically distinct thalamic and cortical cell models converted to NeuroML.

Figure 9

doi: https://doi.org/10.1371/journal.pcbi.1000815.g009