Simulations of modulation of HCN channels in L5PCs (Mäki-Marttunen and Mäki-Marttunen, 2022)

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Accession:267293
"... In this work, we build upon existing biophysically detailed models of thick-tufted layer V pyramidal cells and model the effects of over- and under-expression of Ih channels as well as their neuromodulation by dopamine (gain of Ih function) and acetylcholine (loss of Ih function). We show that Ih channels facilitate the action potentials of layer V pyramidal cells in response to proximal dendritic stimulus while they hinder the action potentials in response to distal dendritic stimulus at the apical dendrite. We also show that the inhibitory action of the Ih channels in layer V pyramidal cells is due to the interactions between Ih channels and a hot zone of low voltage-activated Ca2+ channels at the apical dendrite. Our simulations suggest that a combination of Ih-enhancing neuromodulation at the proximal apical dendrite and Ih-inhibiting modulation at the distal apical dendrite can increase the layer V pyramidal excitability more than any of the two neuromodulators alone..."
Reference:
1 . Mäki-Marttunen T, Mäki-Marttunen V (2022) Excitatory and inhibitory effects of HCN channel modulation on excitability of layer V pyramidal cells Plos Comp Biol [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex layer 5 pyramidal cell;
Channel(s):
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Gene(s):
Transmitter(s): Acetylcholine; Dopamine; Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Neuromodulation;
Implementer(s): Maki-Marttunen, Tuomo [tuomomm at uio.no];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; Acetylcholine; Dopamine; Gaba; Glutamate;
: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 & Alonso 1999
:Comment: corrected rates using q10 = 2.3, target temperature 34, orginal 21

NEURON	{
	SUFFIX Nap_Et2
	USEION na READ ena WRITE ina
	RANGE gNap_Et2bar, gNap_Et2, ina, offm, slom, offma, offmb, sloma, slomb, tauma, taumb, taummax, offh, sloh, offha, offhb, sloha, slohb, tauha, tauhb, tauhmax
}

UNITS	{
	(S) = (siemens)
	(mV) = (millivolt)
	(mA) = (milliamp)
}

PARAMETER	{
	gNap_Et2bar = 0.00001 (S/cm2)
	offm = -52.6 (mV)
	slom = 4.6 (mV)
	offma = -38 (mV)
	offmb = -38 (mV)
	sloma = 6.0 (mV)
	slomb = 6.0 (mV)
	tauma = 5.49451
	taumb = 8.06452
	taummax = 6.0 (ms)
	offh = -48.8 (mV)
	sloh = 10.0 (mV)
	offha = -17 (mV)
	offhb = -64.4 (mV)
	sloha = 4.63 (mV)
	slohb = 2.63 (mV)
	tauha = 347222.2
	tauhb = 144092.2
	tauhmax = 1.0 (ms)
}

ASSIGNED	{
	v	(mV)
	ena	(mV)
	ina	(mA/cm2)
	gNap_Et2	(S/cm2)
	mInf
	mTau
	mAlpha
	mBeta
	hInf
	hTau
	hAlpha
	hBeta
}

STATE	{
	m
	h
}

BREAKPOINT	{
	SOLVE states METHOD cnexp
	gNap_Et2 = gNap_Et2bar*m*m*m*h
	ina = gNap_Et2*(v-ena)
}

DERIVATIVE states	{
	rates()
	m' = (mInf-m)/mTau
	h' = (hInf-h)/hTau
}

INITIAL{
	rates()
	m = mInf
	h = hInf
}

PROCEDURE rates(){
  LOCAL qt
  qt = 2.3^((34-21)/10)

	UNITSOFF
	mInf = 1.0/(1+exp((offm-v)/slom))
        if(v == offma){
    	    v = v+0.0001
        }
        if(v == offmb){
    	    v = v+0.0001
        }
	mAlpha = -(offma-v)/(1-(exp((offma-v)/sloma)))/tauma
	mBeta  = (offmb-v)/(1-(exp(-(offmb-v)/slomb)))/taumb
	mTau = taummax*(1/(mAlpha + mBeta))/qt

  	if(v == offha){
   	    v = v + 0.0001
  	}
        if(v == offhb){
            v = v+0.0001
        }

	hInf = 1.0/(1+exp(-(offh-v)/sloh))
        hAlpha = (offha-v) / (1 - exp(-(offha-v)/sloha))/tauha
        hBeta = -(offhb-v) / (1 - exp((offhb-v)/slohb))/tauhb
	hTau = tauhmax*(1/(hAlpha + hBeta))/qt
	UNITSON
}

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