NML2: Instance-Based Network

Network with explicit instance placement and coordinates

NML2_InstanceBasedNetwork.nml

Demonstrates <instance> elements within a population, giving each cell explicit 3D coordinates for spatial positioning:

<population id="pop0" component="iaf0" size="3" type="populationList">
  <instance id="0"> <location x="0" y="0" z="0"/> </instance>
  <instance id="1"> <location x="100" y="0" z="0"/> </instance>
  <instance id="2"> <location x="0" y="100" z="0"/> </instance>
</population>

from pathlib import Path

nml_file = Path.home() / "work_data/toolboxes/NeuroML2/examples/NML2_InstanceBasedNetwork.nml"
text = nml_file.read_text()

# Show network structure
in_network = False
for line in text.split('\n'):
    if '<network' in line:
        in_network = True
    if in_network:
        print(line.rstrip()[:100])
    if '</network' in line:
        break

    <network id="InstanceBasedNetwork">

        <population id="iafCells" type="populationList" component="iaf" size="3">
            <instance id="0">
                <location x="120" y="230" z="567"/>
            </instance>
            <instance id="1">
                <location x="270" y="450" z="56"/>
            </instance>
            <instance id="2">
                <location x="54" y="234" z="89"/>
            </instance>
        </population>


        <projection id="internal1" presynapticPopulation="iafCells" postsynapticPopulation="iafCells
            <!--TODO: Fix! want to define synapse in here, so that multiple synapses per connection 
            <synapseComponent component="syn1"/>-->
            <!--TODO: Fix! want to use preCellId="0"  -->
            <connection id="0" preCellId="../iafCells/0/iaf" postCellId="../iafCells/1/iaf"/>
        </projection>

        <projection id="internal2" presynapticPopulation="iafCells" postsynapticPopulation="iafCells
            <connection id="0" preCellId="../iafCells/0/iaf" postCellId="../iafCells/2/iaf"/>
        </projection>


        <inputList id="stimInput" component="pulseGen1" population="iafCells">
            <!--TODO: Fix! want to use target="0"  -->
            <input id="0" target="../iafCells/0/iaf" destination="synapses"/>
        </inputList>


    </network>

TVBO Representation: IaF Cell

from tvbo import SimulationExperiment

exp = SimulationExperiment.from_string("""
label: "NML2 InstanceBasedNetwork: IaF Cell"
dynamics:
  name: IntegrateAndFire
  parameters:
    leakReversal: { value: -50.0 }
    tau:          { value: 30.0 }
    thresh:       { value: -55.0 }
    reset:        { value: -70.0 }
  state_variables:
    v:
      equation: { rhs: "(leakReversal - v) / tau" }
      initial_value: -50.0
      variable_of_interest: true
  events:
    spike:
      condition: { rhs: "v > thresh" }
      affect:    { rhs: "v = reset" }
network:
  number_of_nodes: 1
integration:
  method: euler
  step_size: 0.005
  duration: 300.0
  time_scale: ms
""")
xml = exp.render("lems")
print(xml[:800])

<Lems>

  <!-- Tell jLEMS/jNeuroML which component is the simulation entry point. -->
  <Target component="sim_NML2_InstanceBasedNetwork__IaF_Cell"/>

  <!-- ════════════════════════════════════════════════════════════════
       Dimensions & Units (inline — no external includes needed)
       ════════════════════════════════════════════════════════════════ -->

  <!-- Dimensions -->
  <Dimension name="none"/>
  <Dimension name="time" t="1"/>
  <Dimension name="voltage" m="1" l="2" t="-3" i="-1"/>
  <Dimension name="per_time" t="-1"/>
  <Dimension name="conductance" m="-1" l="-2" t="3" i="2"/>
  <Dimension name="capacitance" m="-1" l="-2" t="4" i="2"/>
  <Dimension name="current" i="1"/>
  <Dimension name="resistance" m="1" l="2" t="-3" i="-2"/>
  <Dimension name="concentration" l="-3" n=

Run TVBO

import numpy as np
import matplotlib.pyplot as plt

result = exp.run("neuroml")
da = result.integration.data
t = da.coords['time'].values
v = da.values[:, 0]

fig, ax = plt.subplots(figsize=(10, 4))
ax.plot(t, v)
ax.set_xlabel("Time (ms)")
ax.set_ylabel("Voltage (mV)")
ax.set_title("NML2 InstanceBasedNetwork: IaF Cell via TVBO")
ax.grid(True, alpha=0.3)
plt.tight_layout()
plt.show()