Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)

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Accession:185858
"Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. ..."
Reference:
1 . Neymotin SA, McDougal RA, Bulanova AS, Zeki M, Lakatos P, Terman D, Hines ML, Lytton WW (2016) Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex Neuroscience 316:344-366 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Synapse; Channel/Receptor; Molecular Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic cell; Neocortex V1 L2/6 pyramidal intratelencephalic cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex layer 2-3 interneuron; Neocortex layer 5 interneuron; Neocortex layer 6a interneuron;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I CAN; I Calcium; I_AHP; I_KD; Ca pump;
Gap Junctions:
Receptor(s): mGluR1; GabaA; GabaB; AMPA; NMDA; mGluR; Glutamate; Gaba; IP3;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Ion Channel Kinetics; Oscillations; Spatio-temporal Activity Patterns; Signaling pathways; Working memory; Attractor Neural Network; Calcium dynamics; Laminar Connectivity; G-protein coupled; Rebound firing; Brain Rhythms; Dendritic Bistability; Reaction-diffusion; Beta oscillations; Persistent activity; Multiscale;
Implementer(s): Neymotin, Sam [samn at neurosim.downstate.edu]; McDougal, Robert [robert.mcdougal at yale.edu];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic cell; Neocortex V1 L2/6 pyramidal intratelencephalic cell; Neocortex V1 interneuron basket PV cell; mGluR1; GabaA; GabaB; AMPA; NMDA; mGluR; Glutamate; Gaba; IP3; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I CAN; I Calcium; I_AHP; I_KD; Ca pump; Gaba; Glutamate;
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CaHDemo
readme.html
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aux_fun.inc *
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geom.py
ghk.inc *
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init.hoc
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local.hoc *
misc.h
mpisim.py
netcfg.cfg
nqs.hoc
nqs.py
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onepyr.cfg
onepyr.py
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python.hoc *
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screenshot.png
screenshot1.png
simctrl.hoc *
simdat.py
syncode.hoc *
xgetargs.hoc *
                            
: $Id: km.mod,v 1.5 2004/06/08 21:07:12 billl Exp $

COMMENT
26 Ago 2002 Modification of original channel to allow variable time step and to correct an initialization error.
Done by Michael Hines(michael.hines@yale.e) and Ruggero Scorcioni(rscorcio@gmu.edu) at EU Advance Course in Computational Neuroscience. Obidos, Portugal

km.mod

Potassium channel, Hodgkin-Huxley style kinetics
Based on I-M (muscarinic K channel)
Slow, noninactivating

Author: Zach Mainen, Salk Institute, 1995, zach@salk.edu

ENDCOMMENT

NEURON {
  SUFFIX km
  USEION k READ ek WRITE ik
  RANGE n, gk, gmax, i
  RANGE ninf, ntau, tadj
  GLOBAL Ra, Rb
  GLOBAL q10, temp, vmin, vmax
}

UNITS {
  (mA) = (milliamp)
  (mV) = (millivolt)
  (pS) = (picosiemens)
  (um) = (micron)
} 

PARAMETER {
  gmax = 10   	(pS/um2)	: 0.03 mho/cm2
  v 		(mV)
  
  tha  = -30	(mV)		: v 1/2 for inf
  qa   = 9	(mV)		: inf slope		
  
  Ra   = 0.001	(/ms)		: max act rate  (slow)
  Rb   = 0.001	(/ms)		: max deact rate  (slow)

  dt		(ms)
  celsius		(degC)
  temp = 23	(degC)		: original temp 	
  q10  = 2.3			: temperature sensitivity

  vmin = -120	(mV)
  vmax = 100	(mV)
} 


ASSIGNED {
  a		(/ms)
  b		(/ms)
  i 		(mA/cm2)
  ik 		(mA/cm2)
  gk		(pS/um2)
  ek		(mV)
  ninf
  ntau (ms)	
  tadj
}

STATE { n }

INITIAL { 
  tadj = q10^((celsius - temp)/10)
  rates(v)
  n = ninf
}

BREAKPOINT {
  SOLVE states METHOD cnexp
  gk = tadj*gmax*n
  i = (1e-4) * gk * (v - ek)
  ik = i
} 

LOCAL nexp

DERIVATIVE states {   :Computes state variable n 
  rates(v)      :             at the current v and dt.
  n' = (ninf-n)/ntau

}

PROCEDURE rates(v) {  :Computes rate and other constants at current v.
  :Call once from HOC to initialize inf at resting v.

  a = Ra * (v - tha) / (1 - exp(-(v - tha)/qa))
  b = -Rb * (v - tha) / (1 - exp((v - tha)/qa))

  ntau = 1/tadj/(a+b)
  ninf = a/(a+b)
}


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