Nap.channel.nml 3.9 KB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576
  1. <?xml version="1.0" encoding="ISO-8859-1"?>
  2. <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">
  3. <notes>NeuroML file containing a single Channel description</notes>
  4. <ionChannel id="Nap" conductance="10pS" type="ionChannelHH" species="na">
  5. <notes>Persistent Na+ current
  6. Comment from original mod file:
  7. :Comment : mtau deduced from text (said to be 6 times faster than for NaTa)
  8. :Comment : so I used the equations from NaT and multiplied by 6
  9. :Reference : Modeled according to kinetics derived from Magistretti and Alonso 1999
  10. :Comment: corrected rates using q10 = 2.3, target temperature 34, orginal 21</notes>
  11. <annotation>
  12. <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
  13. <rdf:Description rdf:about="Nap">
  14. <bqmodel:isDescribedBy xmlns:bqmodel="http://biomodels.net/model-qualifiers/">
  15. <rdf:Bag>
  16. <rdf:li>Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties,
  17. Etay Hay, Sean Hill, Felix Schürmann, Henry Markram and Idan Segev, PLoS Comp Biol 2011</rdf:li>
  18. <rdf:li rdf:resource="http://www.ncbi.nlm.nih.gov/pubmed/21829333"/>
  19. </rdf:Bag>
  20. </bqmodel:isDescribedBy>
  21. <bqbiol:isVersionOf xmlns:bqbiol="http://biomodels.net/biology-qualifiers/">
  22. <rdf:Bag>
  23. <rdf:li>Na channels</rdf:li>
  24. <rdf:li rdf:resource="http://senselab.med.yale.edu/neurondb/channelGene2.aspx#table2"/>
  25. </rdf:Bag>
  26. </bqbiol:isVersionOf>
  27. </rdf:Description>
  28. </rdf:RDF>
  29. </annotation>
  30. <gate id="m" type="gateHHratesTauInf" instances="3">
  31. <q10Settings type="q10Fixed" fixedQ10="2.95288264"/>
  32. <forwardRate type="HHExpLinearRate" rate="1.092per_ms" scale="6mV" midpoint="-38mV"/>
  33. <reverseRate type="HHExpLinearRate" rate="0.744per_ms" scale="-6mV" midpoint="-38mV"/>
  34. <timeCourse type="Nap_m_tau_tau"/>
  35. <steadyState type="HHSigmoidVariable" rate="1" scale="4.6mV" midpoint="-52.6mV"/>
  36. </gate>
  37. <gate id="h" type="gateHHratesInf" instances="1">
  38. <q10Settings type="q10Fixed" fixedQ10="2.95288264"/>
  39. <forwardRate type="HHExpLinearRate" rate="1.33344e-05per_ms" scale="-4.63mV" midpoint="-17mV"/>
  40. <reverseRate type="HHExpLinearRate" rate="1.82522e-05per_ms" scale="2.63mV" midpoint="-64.4mV"/>
  41. <steadyState type="HHSigmoidVariable" rate="1" scale="-10mV" midpoint="-48.8mV"/>
  42. </gate>
  43. </ionChannel>
  44. <ComponentType name="Nap_m_tau_tau" extends="baseVoltageDepTime">
  45. <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
  46. <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
  47. <Requirement name="alpha" dimension="per_time"/>
  48. <Requirement name="beta" dimension="per_time"/>
  49. <Dynamics>
  50. <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
  51. <DerivedVariable name="ALPHA" dimension="none" value="alpha * TIME_SCALE"/>
  52. <DerivedVariable name="BETA" dimension="none" value="beta * TIME_SCALE"/>
  53. <ConditionalDerivedVariable name="t" exposure="t" dimension="time">
  54. <Case condition="(ALPHA + BETA) .eq. 0" value="( 0 ) * TIME_SCALE"/>
  55. <Case condition="(ALPHA + BETA) .gt. ( 0 )" value="( 6/( (ALPHA + BETA) ) ) * TIME_SCALE"/>
  56. <Case value="( 0) * TIME_SCALE"/>
  57. </ConditionalDerivedVariable>
  58. </Dynamics>
  59. </ComponentType>
  60. </neuroml>