Ex6: NMDA Synapse

Cell with morphology receiving NMDA synapse input and DC current

Model: NMDA Synapse

A passive cell (with morphology and biophysics) receives NMDA synapse input from a spike generator, plus a DC current injection. Demonstrates the cell type with channelDensity and blockingPlasticSynapse with Mg²⁺ block.

Reference: NeuroML2 LEMS_NML2_Ex6_NMDA.xml

---

1. Define Network in TVBO

from tvbo import SimulationExperiment

exp = SimulationExperiment.from_string("""
label: "NeuroML Ex6: NMDA Synapse"
network:
  dynamics:
    passiveCell:
      name: passiveCell
      iri: neuroml:cell
      parameters:
        diameter: {value: 17.841242}
        specificCapacitance: {value: 1.0, unit: uF_per_cm2}
        initMembPotential: {value: -65, unit: mV}
        spikeThresh: {value: -20, unit: mV}
        resistivity: {value: 0.03, unit: kohm_cm}
      components:
        passiveChan:
          name: passiveChan
          iri: neuroml:ionChannelHH
          parameters:
            conductance: {value: 10, unit: pS}
            condDensity: {value: 0.0003, unit: S_per_cm2}
            erev: {value: -54.3, unit: mV}
            ion: {description: non_specific}
    spikeGen75ms:
      name: spikeGen75ms
      iri: neuroml:spikeGenerator
      parameters:
        period: {value: 75, unit: ms}
    nmdaSyn1:
      name: nmdaSyn1
      iri: neuroml:blockingPlasticSynapse
      parameters:
        gbase: {value: 0.5, unit: nS}
        erev: {value: 0, unit: mV}
        tauRise: {value: 2, unit: ms}
        tauDecay: {value: 8, unit: ms}
      modes:
        blockMechanism:
          name: blockMechanism
          iri: neuroml:voltageConcDepBlockMechanism
          parameters:
            species: {description: mg}
            blockConcentration: {value: 1.2, unit: mmol_per_m3}
            scalingConc: {value: 1.920544, unit: mmol_per_m3}
            scalingVolt: {value: 16.129, unit: mV}
    pulseGen2:
      name: pulseGen2
      iri: neuroml:pulseGenerator
      parameters:
        delay: {value: 200, unit: ms}
        duration: {value: 10000, unit: ms}
        amplitude: {value: 0.065, unit: nA}
  nodes:
    - {id: 0, dynamics: passiveCell}
    - {id: 10, dynamics: spikeGen75ms}
    - {id: 100, dynamics: pulseGen2}
  edges:
    - {source: 10, target: 0, coupling: nmdaSyn1}
    - {source: 100, target: 0}
integration:
  method: euler
  step_size: 0.01
  duration: 400.0
  time_scale: ms
""")
print(f"TVBO model: {exp.dynamics.name if exp.dynamics else "network"}")

TVBO model: network

2. Render LEMS XML

xml = exp.render("lems")
print(xml[:3000])

<Lems>
  <Target component="sim_NeuroML_Ex6__NMDA_Synapse"/>

  <Include file="Cells.xml"/>
  <Include file="Networks.xml"/>
  <Include file="Inputs.xml"/>
  <Include file="Simulation.xml"/>

    <ionChannelHH id="passiveChan" conductance="10 pS"/>

    <cell id="passiveCell">
        <morphology id="passiveCell_morphology">
            <segment id="0" name="Soma">
                <proximal x="0.0" y="0.0" z="0.0" diameter="17.841242"/>
                <distal x="0.0" y="0.0" z="0.0" diameter="17.841242"/>
            </segment>
            <segmentGroup id="all">
                <member segment="0"/>
            </segmentGroup>
            <segmentGroup id="soma_group">
                <member segment="0"/>
            </segmentGroup>
        </morphology>
        <biophysicalProperties id="biophys">
            <membraneProperties>
                <channelDensity condDensity="0.0003 S_per_cm2" id="passiveChan_all" ionChannel="passiveChan" erev="-54.3 mV" ion="non_specific"/>
                <specificCapacitance value="1 uF_per_cm2"/>
                <initMembPotential value="-65 mV"/>
                <spikeThresh value="-20 mV"/>
            </membraneProperties>
            <intracellularProperties>
                <resistivity value="0.03 kohm_cm"/>
            </intracellularProperties>
        </biophysicalProperties>
    </cell>

    <spikeGenerator id="spikeGen75ms" period="75.0 ms"/>

    <pulseGenerator id="pulseGen2" amplitude="0.065 nA" delay="200.0 ms" duration="10000.0 ms"/>

    <blockingPlasticSynapse id="nmdaSyn1" erev="0 mV" gbase="0.5 nS" tauDecay="8 ms" tauRise="2 ms">
        <blockMechanism type="voltageConcDepBlockMechanism" blockConcentration="1.2 mM" scalingConc="1.920544 mM" scalingVolt="16.129 mV" species="mg"/>
    </blockingPlasticSynapse>

    <network id="net1">
        <population id="passiveCell_pop" component="passiveCell" size="1"/>
        <population id="spikeGen75ms_pop" component="spikeGen75ms" size="1"/>
        <synapticConnection from="spikeGen75ms_pop[0]" to="passiveCell_pop[0]" synapse="nmdaSyn1" destination="synapses"/>
        <explicitInput target="passiveCell_pop[0]" input="pulseGen2" destination="synapses"/>
    </network>

    <Simulation id="sim_NeuroML_Ex6__NMDA_Synapse" length="400.0ms" step="0.01ms" target="net1">
        <OutputFile id="of0" fileName="results/passiveCell.dat">
            <OutputColumn id="passiveCell_pop_0_v" quantity="passiveCell_pop[0]/v"/>
        </OutputFile>
    </Simulation>

</Lems>

3. Run Reference

from tvbo.adapters.neuroml import run_lems_example

ref_outputs = run_lems_example("LEMS_NML2_Ex6_NMDA.xml")
for name, arr in ref_outputs.items():
    print(f"  {name}: shape={arr.shape}")

  ex6_block.dat: shape=(40001, 2)
  ex6_g.dat: shape=(40001, 2)
  ex6_v.dat: shape=(40001, 2)

4. Run TVBO

result = exp.run("neuroml")
da = result.integration.data
print(f"TVBO: {da.dims}, shape={da.shape}")

TVBO: ('time', 'quantity'), shape=(40001, 1)

5. Compare & Plot

from tvbo.adapters.neuroml import plot_lems_comparison
plot_lems_comparison("LEMS_NML2_Ex6_NMDA.xml", ref_outputs, result.integration.data, title_prefix="Ex6")