Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells (Lee et al. 2014)

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Accession:153280
This detailed microcircuit model explores the network level effects of sublayer specific connectivity in the mouse CA1. The differences in strengths and numbers of synapses between PV+ basket cells and either superficial sublayer or deep sublayer pyramidal cells enables a routing of inhibition from superficial to deep pyramidal cells. At the network level of this model, the effects become quite prominent when one compares the effect on firing rates when either the deep or superficial pyramidal cells receive a selective increase in excitation.
Reference:
1 . Lee SH, Marchionni I, Bezaire M, Varga C, Danielson N, Lovett-Barron M, Losonczy A, Soltesz I (2014) Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells. Neuron 82:1129-44 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 basket cell;
Channel(s): I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; Glutamate;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Connectivity matrix; Laminar Connectivity;
Implementer(s): Bezaire, Marianne [mariannejcase at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; Glutamate; I Sodium; I Calcium; I Potassium;
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ch_CavN.mod
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ch_Kdrfast.mod
ch_Kdrp.mod
ch_Kdrslow.mod
ch_KvA.mod
ch_KvAdistp.mod
ch_KvAproxp.mod
ch_KvCaB.mod
ch_leak.mod
ch_Navp.mod
ch_NavPVBC.mod
iconc_Ca.mod
iconc_CaZ.mod
MyExp2Sid.mod
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mynetstim.mod *
repeatconn.mod
hg_diff.out *
hg_status.out *
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version.txt *
                            
TITLE K-A channel from Klee Ficker and Heinemann
: modified to account for Dax A Current --- M.Migliore Jun 1997
: modified to be used with cvode  M.Migliore 2001

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)

}

PARAMETER {
	v (mV)
	celsius		(degC)
	gmax=.008 (mho/cm2)
	vhalfn=11   (mV)
	vhalfl=-56   (mV)
	a0l=0.05      (/ms)
	a0n=0.05    (/ms)
	zetan=-1.5    (1)
	zetal=3    (1)
	gmn=0.55   (1)
	gml=1   (1)
	lmin=2  (mS)
	nmin=0.1  (mS)
	pw=-1    (1)
	tq=-40
	qq=5
	q10=5
	qtl=1
	ek
	e
}


NEURON {
	SUFFIX ch_KvAproxp
	USEION k READ ek WRITE ik
	RANGE gmax, myi, e
	GLOBAL ninf,linf,taul,taun,lmin
}

STATE {
	n
        l
}

ASSIGNED {
	ik (mA/cm2)
	myi (mA/cm2)
	ninf
	linf      
	taul
	taun
	g
}

INITIAL {
	rates(v)
	n=ninf
	l=linf
}


BREAKPOINT {
	SOLVE states METHOD cnexp
	g = gmax*n*l
	ik = g*(v-ek)
	myi = ik
}


FUNCTION alpn(v(mV)) {
LOCAL zeta
  zeta=zetan+pw/(1+exp((v-tq)/qq))
  alpn = exp(1.e-3*zeta*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION betn(v(mV)) {
LOCAL zeta
  zeta=zetan+pw/(1+exp((v-tq)/qq))
  betn = exp(1.e-3*zeta*gmn*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION alpl(v(mV)) {
  alpl = exp(1.e-3*zetal*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION betl(v(mV)) {
  betl = exp(1.e-3*zetal*gml*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 
}

DERIVATIVE states {     : exact when v held constant; integrates over dt step
        rates(v)
        n' = (ninf - n)/taun
        l' =  (linf - l)/taul
}

PROCEDURE rates(v (mV)) { :callable from hoc
        LOCAL a,qt
        qt=q10^((celsius-24)/10)
        a = alpn(v)
        ninf = 1/(1 + a)
        taun = betn(v)/(qt*a0n*(1+a))
	if (taun<nmin) {taun=nmin}
        a = alpl(v)
        linf = 1/(1+ a)
	taul = 0.26*(v+50)/qtl
	if (taul<lmin/qtl) {taul=lmin/qtl}
}