wip: KC conversion

OpenSourceBrain · Apr 9, 2024 · 7532ea8 · 7532ea8
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diff --git a/NEURON/mb/mod/Steady_state(s)_of_activation_variables_in_nas_at_6.3_degC.png b/NEURON/mb/mod/Steady_state(s)_of_activation_variables_in_nas_at_6.3_degC.png
diff --git a/NEURON/mb/mod/Time_course(s)_of_activation_variables_in_nas_at_6.3_degC.png b/NEURON/mb/mod/Time_course(s)_of_activation_variables_in_nas_at_6.3_degC.png
diff --git a/NeuroML2/GGN.cell.nml b/NeuroML2/GGN.cell.nml
diff --git a/NeuroML2/GGM.morph.cell.nml → NeuroML2/GGN.morph.cell.nml b/NeuroML2/GGM.morph.cell.nml → NeuroML2/GGN.morph.cell.nml
diff --git a/NeuroML2/channels/nas.channel.nml b/NeuroML2/channels/nas.channel.nml
@@ -0,0 +1,137 @@
+<?xml version="1.0" encoding="ISO-8859-1"?>
+<neuroml xmlns="http://www.neuroml.org/schema/neuroml2" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2beta4.xsd" id="NeuroML_ionChannel">
+
+    <notes>NeuroML file containing a single ion channel</notes>
+
+    <ionChannel id="Navp" conductance="1pS" type="ionChannelHH" species="na">
+
+        <notes>
+            Implementation of slow Na+ channel ( NAS ) from Wustenberg DG, Boytcheva M, Grunewald B, Byrne JH, Menzel R, Baxter DA
+
+            This is slow Na+ channel in Apis mellifera Kenyon cells :(cultured).
+        </notes>
+
+        <gate id="m" type="gateHHratesTau" instances="3">
+            <forwardRate type="HHExpLinearRate" rate="1per_ms" midpoint="-30.1mV" scale="6.65mV"/>
+            <timeCourse type="Ray_nas_taum"/>
+        </gate>
+
+        <gate id="h" type="gateHHratesTau" instances="1">
+            <forwardRate type="HHExpLinearRate" rate="1per_ms" midpoint="-51.4mV" scale="5.9mV"/>
+            <timeCourse type="Ray_nas_tauh"/>
+        </gate>
+
+    </ionChannel>
+
+     <ComponentType name="Ray_nas_taum"
+                   extends="baseVoltageDepTime"
+                   description="Tau parameter to describe Navp">
+
+        <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
+        <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
+        <Constant name="max_tau" dimension="per_time" value="0.83 per_time"/>
+        <Constant name="min_tau" dimension="per_time" value="0.093 per_time"/>
+        <Dynamics>
+            <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
+            <ConditionalDerivedVariable name="t" dimension="time" exposure="t">
+                <Case condition="(ALPHA + BETA) .eq. 0" value="( 0 ) * TIME_SCALE"/>
+                <Case condition="1/( (ALPHA + BETA) * rateScale )  .lt. ( 0.02 )" value="( (0.02 * rateScale) ) * TIME_SCALE"/>
+                <Case value="( 1/(ALPHA + BETA) ) * TIME_SCALE"/>
+            </ConditionalDerivedVariable>
+
+        </Dynamics>
+
+    </ComponentType>
+
+    <ComponentType name="Ray_nas_tauh"
+                   extends="baseVoltageDepTime"
+                   description="Tau parameter to describe Navp">
+
+        <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
+        <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
+
+        <Requirement name="alpha" dimension="per_time"/>
+        <Requirement name="beta" dimension="per_time"/>
+        <Requirement name="rateScale" dimension="none"/>
+
+        <Dynamics>
+            <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
+            <DerivedVariable name="ALPHA" dimension="none" value="alpha * TIME_SCALE"/>
+            <DerivedVariable name="BETA" dimension="none" value="beta * TIME_SCALE"/>
+
+            <ConditionalDerivedVariable name="t" exposure="t" dimension="time">
+                <Case condition="(ALPHA + BETA) .eq. 0" value="( 0 ) * TIME_SCALE"/>
+                <Case condition="1/( (ALPHA + BETA) * rateScale )  .lt. ( 0.5 )" value="( (0.5 * rateScale) ) * TIME_SCALE"/>
+                <Case value="( 1/(ALPHA + BETA) ) * TIME_SCALE"/>
+            </ConditionalDerivedVariable>
+
+        </Dynamics>
+
+    </ComponentType>
+
+    <ComponentType name="Ray_nas_taus"
+                   extends="baseVoltageDepTime"
+                   description="Tau parameter to describe Navp">
+
+        <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
+        <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
+        <Constant name="TEMP_SCALE" dimension="temperature" value="1 K"/>
+        <Constant name="R" dimension="none" value="8.315"/>
+        <Constant name="F" dimension="none" value="96480"/>
+
+        <Requirement name="rateScale" dimension="none"/>
+        <Requirement name="temperature" dimension="temperature"/>
+
+        <Dynamics>
+            <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
+            <DerivedVariable name="T" dimension="none" value="temperature / TEMP_SCALE"/>
+
+            <DerivedVariable name="alpha" dimension="none" value="exp((1e-3*12*(V+45)*F) / (R*(T+0.01)))"/> <!-- NEURON code: 273.16 + celsius-->
+            <DerivedVariable name="beta" dimension="none" value="exp((1e-3*12*0.2*(V+45)*F) / (R*(T+0.01)))"/> <!-- NEURON code: 273.16 + celsius-->
+
+            <DerivedVariable name="tmp" value="beta / (3e-4*(1 + alpha))" dimension="none"/>
+            <ConditionalDerivedVariable name="t" dimension="time" exposure="t" >
+                <Case condition="(tmp / rateScale) .lt. 10" value="10 * rateScale * TIME_SCALE"/>
+                <Case value="tmp * TIME_SCALE"/>
+            </ConditionalDerivedVariable>
+
+        </Dynamics>
+
+    </ComponentType>
+
+    <ComponentType name="Ray_nas_sss_ar2_1"
+                   extends="baseVoltageDepVariable"
+                   description="steadyState parameter to describe Navp">
+
+        <Constant name="no_inact" dimension="none" value="1"/> <!-- 1: no inact, 0: max inact-->
+        <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
+
+        <Dynamics>
+            <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
+
+            <DerivedVariable name="alpha" dimension="none" value="1 / (1 + exp((V+43)/2))"/>
+
+            <DerivedVariable name="x" exposure="x" dimension="none" value="alpha + no_inact*(1 - alpha)"/>
+        </Dynamics>
+
+    </ComponentType>
+
+
+    <ComponentType name="Ray_nas_sss_ar2_0_8"
+                   extends="baseVoltageDepVariable"
+                   description="steadyState parameter to describe Navp">
+
+        <Constant name="no_inact" dimension="none" value="0.8"/> <!-- 1: no inact, 0: max inact-->
+        <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
+
+        <Dynamics>
+            <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
+
+            <DerivedVariable name="alpha" dimension="none" value="1 / (1 + exp((V+43)/2))"/>
+
+            <DerivedVariable name="x" exposure="x" dimension="none" value="alpha + no_inact*(1 - alpha)"/>
+        </Dynamics>
+
+    </ComponentType>
+
+</neuroml>
diff --git a/NeuroML2/channels/pas.channel.nml b/NeuroML2/channels/pas.channel.nml
@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="ISO-8859-1"?>
+<neuroml xmlns="http://www.neuroml.org/schema/neuroml2" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2beta4.xsd" id="pas">
+
+    <notes>NeuroML file containing a single Channel description</notes>
+
+    <ionChannel id="pas" conductance="10pS" type="ionChannelPassive">
+
+        <notes>Simple example of a leak/passive conductance. Note: for GENESIS cells with a single leak conductance,
+        it is better to use the Rm and Em variables for a passive current.</notes>
+
+    </ionChannel>
+
+</neuroml>
diff --git a/NeuroML2/postprocess_cells.py b/NeuroML2/postprocess_cells.py
@@ -65,9 +65,9 @@ def load_and_setup_cell(cellname: str):
     return celldoc
 
 
-def postprocess_GGM():
-    """Post process GGM and add biophysics."""
-    cellname = "GGM"
+def postprocess_GGN():
+    """Post process GGN and add biophysics."""
+    cellname = "GGN"
     celldoc = load_and_setup_cell(cellname)
     cell = celldoc.cells[0]  # type: neuroml.Cell
 
@@ -124,5 +124,70 @@ def postprocess_KC():
     write_neuroml2_file(celldoc, "KC.cell.nml")
 
 
+def KC_create_na_channel():
+    """Create the Na channel.
+
+    This will create the Na channel and save it to a file.
+    It will also validate this file.
+
+    returns: name of the created file
+    """
+    na_channel = component_factory(
+        "IonChannelHH",
+        id="na_channel",
+        notes="Sodium channel for HH cell",
+        conductance="10pS",
+        species="na",
+        validate=False,
+    )
+    gate_m = component_factory(
+        "GateHHRates",
+        id="m",
+        instances="3",
+        notes="m gate for na channel",
+        validate=False,
+    )
+    m_forward_rate = component_factory(
+        "HHRate", type="HHExpLinearRate", rate="1per_ms", midpoint="-40mV", scale="10mV"
+    )
+    m_reverse_rate = component_factory(
+        "HHRate", type="HHExpRate", rate="4per_ms", midpoint="-65mV", scale="-18mV"
+    )
+
+    gate_m.add(m_forward_rate, hint="forward_rate", validate=False)
+    gate_m.add(m_reverse_rate, hint="reverse_rate")
+    na_channel.add(gate_m)
+
+    gate_h = component_factory(
+        "GateHHRates",
+        id="h",
+        instances="1",
+        notes="h gate for na channel",
+        validate=False,
+    )
+    h_forward_rate = component_factory(
+        "HHRate", type="HHExpRate", rate="0.07per_ms", midpoint="-65mV", scale="-20mV"
+    )
+    h_reverse_rate = component_factory(
+        "HHRate", type="HHSigmoidRate", rate="1per_ms", midpoint="-35mV", scale="10mV"
+    )
+    gate_h.add(h_forward_rate, hint="forward_rate", validate=False)
+    gate_h.add(h_reverse_rate, hint="reverse_rate")
+    na_channel.add(gate_h)
+
+    na_channel_doc = component_factory(
+        "NeuroMLDocument", id="na_channel", notes="Na channel for HH neuron"
+    )
+    na_channel_fn = "HH_example_na_channel.nml"
+    na_channel_doc.add(na_channel)
+    na_channel_doc.validate(recursive=True)
+
+    write_neuroml2_file(
+        nml2_doc=na_channel_doc, nml2_file_name=na_channel_fn, validate=True
+    )
+
+    return na_channel_fn
+
+
 if __name__ == "__main__":
-    postprocess_GGM()
+    postprocess_GGN()