it.channel.nml

<?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="it">

    <notes>NeuroML file containing a single Channel description</notes>

    <ionChannel id="it" conductance="10 pS" type="ionChannelHH" species="ca">

        <notes>T-type Ca channel

WARNING: Global parameter "vshift" from modfile has not been implemented.

Comments from original mod file:

T-type Ca channel
ca.mod to lead to thalamic ca current inspired by destexhe and huguenrd
Uses fixed eca instead of GHK eqn
changed from (AS Oct0899)
changed for use with Ri18  (B.Kampa 2005)
	</notes>
                
        <annotation>
            <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
                <rdf:Description rdf:about="it">
                    
                    <bqmodel:isDescribedBy xmlns:bqmodel="http://biomodels.net/model-qualifiers/">
                        <rdf:Bag>
                            <rdf:li>Talamic Ca current inspired by Destexhe and Huguenard. Uses fixed eca instead of GHK equation.</rdf:li>
                            <rdf:li rdf:resource="http://www.ncbi.nlm.nih.gov/pubmed/16837590"/>
                            <rdf:li rdf:resource="https://senselab.med.yale.edu/ModelDB/showmodel.cshtml?model=108458"/>
                        </rdf:Bag>
                    </bqmodel:isDescribedBy>

                    <bqbiol:isVersionOf xmlns:bqbiol="http://biomodels.net/biology-qualifiers/">
                        <rdf:Bag>
                            <rdf:li>Calcium channels</rdf:li>
                            <rdf:li rdf:resource="http://senselab.med.yale.edu/neurondb/channelGene2.aspx#table1"/>
                        </rdf:Bag>
                    </bqbiol:isVersionOf>

                </rdf:Description>
            </rdf:RDF>
        </annotation>

        <gate id="m" type="gateHHtauInf" instances="2">
            <timeCourse type="CaT_m_tau_tau"/>
            <steadyState type="HHSigmoidVariable" rate="1" scale="7.4mV" midpoint="-50mV"/>
        </gate>

        <gate id="h" type="gateHHtauInf" instances="1">
            <timeCourse type="CaT_h_tau_tau"/>
            <steadyState type="HHSigmoidVariable" rate="1" scale="-5.0mV" midpoint="-78mV"/>
        </gate>

    </ionChannel>
    

    <ComponentType name="CaT_m_tau_tau" extends="baseVoltageDepTime">
        <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>

        <Constant name="am" dimension="none" value="3"/>
        <Constant name="vm1" dimension="voltage" value="25 mV"/>
        <Constant name="wm1" dimension="voltage" value="20 mV"/>
        <Constant name="vm2" dimension="voltage" value="100 mV"/>
        <Constant name="wm2" dimension="voltage" value="15 mV"/>
        
        <Dynamics>
            <DerivedVariable name="t" exposure="t" dimension="time" value="( am + 1.0 / ( exp((v+vm1)/wm1) + exp(-(v+vm2)/wm2) ) ) * TIME_SCALE"/>
        </Dynamics>

    </ComponentType>

    <ComponentType name="CaT_h_tau_tau" extends="baseVoltageDepTime">
        <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
        
        <Constant name="ah" dimension="none" value="85"/>
        <Constant name="vh1" dimension="voltage" value="46 mV"/>
        <Constant name="wh1" dimension="voltage" value="4 mV"/>
        <Constant name="vh2" dimension="voltage" value="405 mV"/>
        <Constant name="wh2" dimension="voltage" value="50 mV"/>

        <Dynamics>
            <DerivedVariable name="t" exposure="t" dimension="time" value="( ah + 1.0 / ( exp((v+vh1)/wh1) + exp(-(v+vh2)/wh2) ) ) * TIME_SCALE"/>
        </Dynamics>

    </ComponentType>
    

</neuroml>