<?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="Nap_Et2">

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

    <ionChannel id="Nap_Et2" conductance="10pS" type="ionChannelHH" species="na">

        <notes>Persistent Na+ current
            
Comment from original mod file: 
:Comment : mtau deduced from text (said to be 6 times faster than for NaTa)
:Comment : so I used the equations from NaT and multiplied by 6
:Reference : Modeled according to kinetics derived from Magistretti and Alonso 1999
:Comment: corrected rates using q10 = 2.3, target temperature 34, orginal 21</notes>
                
        <annotation>
            <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
                <rdf:Description rdf:about="Nap_Et2">
                    
                    <bqmodel:isDescribedBy xmlns:bqmodel="http://biomodels.net/model-qualifiers/">
                        <rdf:Bag>
                            <rdf:li>Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties,
            Etay Hay, Sean Hill, Felix Schürmann, Henry Markram and Idan Segev, PLoS Comp Biol 2011</rdf:li>
                            <rdf:li rdf:resource="http://www.ncbi.nlm.nih.gov/pubmed/21829333"/>
                        </rdf:Bag>
                    </bqmodel:isDescribedBy>

                
                    <bqbiol:isVersionOf xmlns:bqbiol="http://biomodels.net/biology-qualifiers/">
                        <rdf:Bag>
                            <rdf:li>Na channels</rdf:li>
                            <rdf:li rdf:resource="http://senselab.med.yale.edu/neurondb/channelGene2.aspx#table2"/>
                        </rdf:Bag>
                    </bqbiol:isVersionOf>

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

        <gate id="m" type="gateHHratesTauInf" instances="3">
            <q10Settings type="q10Fixed" fixedQ10="2.95288264"/>
            <forwardRate type="HHExpLinearRate" rate="1.092per_ms" scale="6mV" midpoint="-38mV"/>
            <reverseRate type="HHExpLinearRate" rate="0.744per_ms" scale="-6mV" midpoint="-38mV"/>
            <timeCourse type="Nap_Et2_m_tau_tau"/>
            <steadyState type="HHSigmoidVariable" rate="1" scale="4.6mV" midpoint="-52.6mV"/>
        </gate>

        <gate id="h" type="gateHHratesInf" instances="1">
            <q10Settings type="q10Fixed" fixedQ10="2.95288264"/>
            <forwardRate type="HHExpLinearRate" rate="1.33344e-05per_ms" scale="-4.63mV" midpoint="-17mV"/>
            <reverseRate type="HHExpLinearRate" rate="1.82522e-05per_ms" scale="2.63mV" midpoint="-64.4mV"/>
            <steadyState type="HHSigmoidVariable" rate="1" scale="-10mV" midpoint="-48.8mV"/>
        </gate>
                            
    </ionChannel>

    <ComponentType name="Nap_Et2_m_tau_tau" extends="baseVoltageDepTime">
        <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"/>

        <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="(ALPHA + BETA)  .gt. ( 0 )" value="( 6/( (ALPHA + BETA) ) ) * TIME_SCALE"/>
                <Case value="( 0) * TIME_SCALE"/>
            </ConditionalDerivedVariable>
        </Dynamics>

    </ComponentType>

</neuroml>