Ex7: Short-Term Plasticity

Tsodyks-Markram short-term plasticity synapses (STD and STF)

Model: Short-Term Plasticity Synapses

A passive cell receives spikes via three synapse types: 1. expTwoSynapse — no plasticity (control) 2. blockingPlasticSynapse with tsodyksMarkramDepMechanism — depression only 3. blockingPlasticSynapse with tsodyksMarkramDepFacMechanism — depression + facilitation

Reference: NeuroML2 LEMS_NML2_Ex7_STP.xml

1. Define Network in TVBO

from tvbo import SimulationExperiment

exp = SimulationExperiment.from_string("""
label: "NeuroML Ex7: STP Synapses"
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}
    spikeGen30ms:
      name: spikeGen30ms
      iri: neuroml:spikeGenerator
      parameters:
        period: {value: 30, unit: ms}
    noStpSyn:
      name: noStpSyn
      iri: neuroml:expTwoSynapse
      parameters:
        gbase: {value: 1, unit: nS}
        erev: {value: 0, unit: mV}
        tauRise: {value: 0.1, unit: ms}
        tauDecay: {value: 40, unit: ms}
    stpSynDep:
      name: stpSynDep
      iri: neuroml:blockingPlasticSynapse
      parameters:
        gbase: {value: 1, unit: nS}
        erev: {value: 0, unit: mV}
        tauRise: {value: 0.1, unit: ms}
        tauDecay: {value: 40, unit: ms}
      modes:
        plasticityMechanism:
          name: plasticityMechanism
          iri: neuroml:tsodyksMarkramDepMechanism
          parameters:
            initReleaseProb: {value: 0.5}
            tauRec: {value: 300, unit: ms}
    stpSynDepFac:
      name: stpSynDepFac
      iri: neuroml:blockingPlasticSynapse
      parameters:
        gbase: {value: 1, unit: nS}
        erev: {value: 0, unit: mV}
        tauRise: {value: 0.1, unit: ms}
        tauDecay: {value: 40, unit: ms}
      modes:
        plasticityMechanism:
          name: plasticityMechanism
          iri: neuroml:tsodyksMarkramDepFacMechanism
          parameters:
            initReleaseProb: {value: 0.5}
            tauFac: {value: 200, unit: ms}
            tauRec: {value: 300, unit: ms}
  nodes:
    - {id: 0, dynamics: passiveCell}
    - {id: 1, dynamics: passiveCell}
    - {id: 2, dynamics: passiveCell}
    - {id: 10, dynamics: spikeGen30ms}
  edges:
    - {source: 10, target: 0, coupling: noStpSyn}
    - {source: 10, target: 1, coupling: stpSynDep}
    - {source: 10, target: 2, coupling: stpSynDepFac}
integration:
  method: euler
  step_size: 0.01
  duration: 300.0
  time_scale: ms
""")
dyn_name = next(iter(exp.network.dynamics)) if exp.network and exp.network.dynamics else 'network'
print(f"TVBO model: {dyn_name}  (source var: exp)")

TVBO model: noStpSyn  (source var: exp)

* Owlready2 * Warning: ignoring cyclic subclass of/subproperty of, involving:
  http://uri.interlex.org/tgbugs/uris/readable/atlas/Space

2. Render LEMS XML

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

<Lems>

  <!-- Tell jLEMS/jNeuroML which component is the simulation entry point. -->
  <Target component="sim_NeuroML_Ex7__STP_Synapses"/>

  <!-- ════════════════════════════════════════════════════════════════
       Standard NeuroML2 type includes for network mode.
       Provides all standard dimensions, units, synapse types, input
       types, network infrastructure, and simulation types.
       ════════════════════════════════════════════════════════════════ -->
  <Include file="Cells.xml"/>
  <Include file="Networks.xml"/>
  <Include file="Simulation.xml"/>

  <!-- ════════════════════════════════════════════════════════════════
       Dynamics ComponentType & Component instances
       ════════════════════════════════════════════════════════════════ -->


  <!-- ── ComponentType: passiveCell ── -->
  <ComponentType name="passiveCell" extends="baseCellMembPot">
    <Parameter name="diameter" dimension="none"/>
    <Parameter name="initMembPotential" dimension="voltage"/>
    <Parameter name="resistivity" dimension="none"/>
    <Parameter name="specificCapacitance" dimension="none"/>
    <Parameter name="spikeThresh" dimension="voltage"/>
    <Constant name="SEC" dimension="time" value="1ms"/>
    <!-- Dynamically attached synapses/inputs from network connections -->
    <Attachments name="synapses" type="basePointCurrent"/>

    <Dynamics>
      <!-- ── Flat dynamics ── -->
      <OnStart>
      </OnStart>
    </Dynamics>
  </ComponentType>

  <Component id="passiveCell_inst" type="passiveCell" diameter="17.841242" initMembPotential="-65 mV" resistivity="0.03" specificCapacitance="1.0" spikeThresh="-20 mV"/>


  <!-- ════════════════════════════════════════════════════════════════
       Built-in/named synapse definitions (no custom ODE dynamics)
       ════════════════════════════════════════════════════════════════ -->
  <!-- Synapse: noStpSyn (noStpSyn) -->
  <noStpSyn id="noStpSyn"/>
  <!-- Synapse: stpSynDep (stpSynDep) -->
  <stpSynDep id="stpSynDep"/>
  <!-- Synapse: stpSynDepFac (stpSynDepFac) -->
  <stpSynDepFac id="stpSynDepFac"/>

  <!-- ════════════════════════════════════════════════════════════════
       Input Sources (pulseGenerator, spikeGenerator, spikeArray, etc.)
       ════════════════════════════════════════════════════════════════ -->
  <spikeGenerator id="spikeGen30ms" period="30 ms"/>

  <!-- ════════════════════════════════════════════════════════════════
       Network
       ════════════════════════════════════════════════════════════════ -->
  <network id="net1">
    <population id="passiveCell_pop" component="passiveCell_inst" size="3"/>
    <population id="spikeGen30ms_pop" component="spikeGen30ms" size="1"/>

    <synapticConnection from="spikeGen30ms_pop[0]" to="passiveCell_pop[0]" synapse="noStpSyn" destination="synapses"/>
    <synapticConnection from="spikeGen30ms_pop[0]" to="passiveCell_pop[1]" synapse="stpSynDep" destination="synapses"/>
    <synapticConnection from="spikeGen30ms_pop[0]" to="passiveC

3. Run Reference

from tvbo.adapters.neuroml import run_lems_example

ref_outputs = run_lems_example("LEMS_NML2_Ex7_STP.xml")
for name, arr in ref_outputs.items():
    print(f"  {name}: shape={arr.shape}")

  ex7_v.dat: shape=(30001, 4)

4. Run TVBO

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

pyNeuroML >>> 13:07:33 - INFO - Loading LEMS file: tvbo_lems_sim.xml and running with jNeuroML
pyNeuroML >>> 13:07:33 - INFO - Executing: (java -Xmx400M  -Djava.awt.headless=true -jar  "/Users/leonmartin_bih/tools/tvbo/.venv/lib/python3.12/site-packages/pyneuroml/utils/./../lib/jNeuroML-0.14.0-jar-with-dependencies.jar"  tvbo_lems_sim.xml  -nogui -I '') in directory: /var/folders/ym/9kw1g21j1nd7kwfn8c0z3st40000gn/T/tmpmaw1rh9u
pyNeuroML >>> 13:07:35 - INFO - Command completed successfully!

TVBO: ('time', 'quantity'), shape=(30001, 3)

5. Compare & Plot

from tvbo.adapters.neuroml import plot_lems_comparison
plot_lems_comparison("LEMS_NML2_Ex7_STP.xml", ref_outputs, result.integration.data, title_prefix="Ex7")