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

Figure 5

Elements in ChannelML.

ChannelML allows expression of models of voltage (and ligand) gated conductances which are dispersed across the cell membrane (in channel_type element), conductances which are concentrated at synaptic contacts (in synapse_type element) and basic models of time varying internal ion concentrations (in ion_concentration element). Distributed conductance descriptions contain a number of gate elements, which describe the transitions between conducting and non conducting states of the channels underlying the conductances. A number of synaptic conductance models are allowed including simple double exponential waveforms, AMPA and NMDA receptor mediated synapses, Short Term Plasticity (STP) models, Spike Timing Dependent Plasticity (STDP) models, and electrical synapses. The ion_concentration element can be used for the simple models of exponentially decaying Ca2+ pools often used in detailed cell models. A detailed description of each of these elements can be found in Supporting Text S1.

Figure 5

doi: https://doi.org/10.1371/journal.pcbi.1000815.g005