Firing patterns of CA3 hippocampal neurons (Soldado-Magraner et al. 2019)

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Accession:228599
" ... Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike-timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions towards adapting and intrinsic burst behaviours, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade, and found that the observed transitions are likely due to recruitment of low-voltage calcium and Kv7 potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits."
Reference:
1 . Soldado-Magraner S, Brandalise F, Honnuraiah S, Pfeiffer M, Moulinier M, Gerber U, Douglas R (2019) Conditioning by Subthreshold Synaptic Input Changes the Intrinsic Firing Pattern of CA3 Hippocampal Neurons. J Neurophysiol [PubMed]
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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: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Activity Patterns; Simplified Models;
Implementer(s): Honnuraiah, Suraj [hs at ini.phys.ethz.ch]; Gutierrez, Adrian [agutie at ini.uzh.ch]; Soldado-Magraner, Saray [ssaray at ini.uzh.ch];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell;
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SoldadoMagranerEtAl2019
readme.html
cacumm.mod
cagk.mod
cal2.mod *
can2.mod *
cat.mod *
kaprox.mod
kd.mod
kd_inc_tau.mod
kdrca1.mod
km.mod *
na3n.mod
sample_requirements.txt
screenshot.png
Single_Compartment_Complete_Conductance_List.txt
single_compartment_SoldadoMagranerEtAl.py
                            
TITLE na3
: Na current 
: modified from Jeff Magee. M.Migliore may97
: added sh to account for higher threshold M.Migliore, Apr.2002

NEURON {
	SUFFIX na3
	USEION na READ ena WRITE ina
	RANGE  gbar, ar, sh, ina
	GLOBAL minf, hinf, mtau, htau, sinf, taus,qinf, thinf
}

PARAMETER {
	sh   = 24	(mV)
	gbar = 0.010   	(mho/cm2)	
								
	tha  =  -30	(mV)		: v 1/2 for act	
	qa   = 7.2	(mV)		: act slope (4.5)		
	Ra   = 0.4	(/ms)		: open (v)		
	Rb   = 0.124 	(/ms)		: close (v)		

	thi1  = -45	(mV)		: v 1/2 for inact 	
	thi2  = -45 	(mV)		: v 1/2 for inact 	
	qd   = 1.5	(mV)	        : inact tau slope
	qg   = 1.5      (mV)
	mmin=0.02	
	hmin=0.5			
	q10=2
	Rg   = 0.01 	(/ms)		: inact recov (v) 	
	Rd   = .03 	(/ms)		: inact (v)	
	qq   = 10        (mV)
	tq   = -55      (mV)

	thinf  = -50 	(mV)		: inact inf slope	
	qinf  = 4 	(mV)		: inact inf slope 

        vhalfs=-60	(mV)		: slow inact.
        a0s=0.0003	(ms)		: a0s=b0s
        zetas=12	(1)
        gms=0.2		(1)
        smax=10		(ms)
        vvh=-58		(mV) 
        vvs=2		(mV)
        ar=1		(1)		: 1=no inact., 0=max inact.
	ena		(mV)            : must be explicitly def. in hoc
	celsius
	v 		(mV)
}


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

ASSIGNED {
	ina 		(mA/cm2)
	thegna		(mho/cm2)
	minf 		hinf 		
	mtau (ms)	htau (ms) 	
	sinf (ms)	taus (ms)
}
 

STATE { m h s}

BREAKPOINT {
        SOLVE states METHOD cnexp
        thegna = gbar*m*m*m*h*s
	ina = thegna * (v - ena)
} 

INITIAL {
	trates(v,ar,sh)
	m=minf  
	h=hinf
	s=sinf
}


FUNCTION alpv(v(mV)) {
         alpv = 1/(1+exp((v-vvh-sh)/vvs))
}
        
FUNCTION alps(v(mV)) {  
  alps = exp(1.e-3*zetas*(v-vhalfs-sh)*9.648e4/(8.315*(273.16+celsius)))
}

FUNCTION bets(v(mV)) {
  bets = exp(1.e-3*zetas*gms*(v-vhalfs-sh)*9.648e4/(8.315*(273.16+celsius)))
}

LOCAL mexp, hexp, sexp

DERIVATIVE states {   
        trates(v,ar,sh)      
        m' = (minf-m)/mtau
        h' = (hinf-h)/htau
        s' = (sinf - s)/taus
}

PROCEDURE trates(vm,a2,sh2) {  
        LOCAL  a, b, c, qt
        qt=q10^((celsius-24)/10)
	a = trap0(vm,tha+sh2,Ra,qa)
	b = trap0(-vm,-tha-sh2,Rb,qa)
	mtau = 1/(a+b)/qt
        if (mtau<mmin) {mtau=mmin}
	minf = a/(a+b)

	a = trap0(vm,thi1+sh2,Rd,qd)
	b = trap0(-vm,-thi2-sh2,Rg,qg)
	htau =  1/(a+b)/qt
        if (htau<hmin) {htau=hmin}
	hinf = 1/(1+exp((vm-thinf-sh2)/qinf))
	c=alpv(vm)
        sinf = c+a2*(1-c)
        taus = bets(vm)/(a0s*(1+alps(vm)))
        if (taus<smax) {taus=smax}
}

FUNCTION trap0(v,th,a,q) {
	if (fabs(v-th) > 1e-6) {
	        trap0 = a * (v - th) / (1 - exp(-(v - th)/q))
	} else {
	        trap0 = a * q
 	}
}