K_P.channel.nml 3.8 KB

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  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="K_P">
  3. <notes>NeuroML file containing a single Channel description</notes>
  4. <ionChannel id="K_P" conductance="10pS" type="ionChannelHH" species="k">
  5. <notes>Slow inactivating K+ current
  6. Comment from original mod file:
  7. :Comment : The persistent component of the K current
  8. :Reference : : Voltage-gated K+ channels in layer 5 neocortical pyramidal neurones from young rats:subtypes and gradients,Korngreen and Sakmann, J. Physiology, 2000
  9. :Comment : shifted -10 mv to correct for junction potential
  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="K_P">
  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>K channels</rdf:li>
  24. <rdf:li rdf:resource="http://senselab.med.yale.edu/neurondb/channelGene2.aspx#table3"/>
  25. </rdf:Bag>
  26. </bqbiol:isVersionOf>
  27. </rdf:Description>
  28. </rdf:RDF>
  29. </annotation>
  30. <gate id="m" type="gateHHtauInf" instances="2">
  31. <q10Settings type="q10Fixed" fixedQ10="2.95288264"/>
  32. <timeCourse type="K_P_m_tau_tau"/>
  33. <steadyState type="HHSigmoidVariable" rate="1" scale="12mV" midpoint="-11mV"/>
  34. </gate>
  35. <gate id="h" type="gateHHtauInf" instances="1">
  36. <q10Settings type="q10Fixed" fixedQ10="2.95288264"/>
  37. <timeCourse type="K_P_h_tau_tau"/>
  38. <steadyState type="HHSigmoidVariable" rate="1" scale="-11mV" midpoint="-64mV"/>
  39. </gate>
  40. </ionChannel>
  41. <ComponentType name="K_P_m_tau_tau" extends="baseVoltageDepTime">
  42. <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
  43. <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
  44. <Dynamics>
  45. <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
  46. <ConditionalDerivedVariable name="t" exposure="t" dimension="time">
  47. <Case condition="V .lt. ( -60 )" value="( (1.25 + 175.03 * (exp ((V+10) * 0.026))) ) * TIME_SCALE"/>
  48. <Case value="( (1.25 + 13 * (exp ((V+10) * -0.026)))) * TIME_SCALE"/>
  49. </ConditionalDerivedVariable>
  50. </Dynamics>
  51. </ComponentType>
  52. <ComponentType name="K_P_h_tau_tau" extends="baseVoltageDepTime">
  53. <Constant name="TIME_SCALE" dimension="time" value="1 ms"/>
  54. <Constant name="VOLT_SCALE" dimension="voltage" value="1 mV"/>
  55. <Dynamics>
  56. <DerivedVariable name="V" dimension="none" value="v / VOLT_SCALE"/>
  57. <DerivedVariable name="t" exposure="t" dimension="time" value="(360 + (1010 + 24*(V+65)) * (exp (-1 *((V+85)/48)*((V+85)/48)))) * TIME_SCALE"/>
  58. </Dynamics>
  59. </ComponentType>
  60. </neuroml>