Linear vs non-linear integration in CA1 oblique dendrites (Gómez González et al. 2011)

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Accession:144450
The hippocampus in well known for its role in learning and memory processes. The CA1 region is the output of the hippocampal formation and pyramidal neurons in this region are the elementary units responsible for the processing and transfer of information to the cortex. Using this detailed single neuron model, it is investigated the conditions under which individual CA1 pyramidal neurons process incoming information in a complex (non-linear) as opposed to a passive (linear) manner. This detailed compartmental model of a CA1 pyramidal neuron is based on one described previously (Poirazi, 2003). The model was adapted to five different reconstructed morphologies for this study, and slightly modified to fit the experimental data of (Losonczy, 2006), and to incorporate evidence in pyramidal neurons for the non-saturation of NMDA receptor-mediated conductances by single glutamate pulses. We first replicate the main findings of (Losonczy, 2006), including the very brief window for nonlinear integration using single-pulse stimuli. We then show that double-pulse stimuli increase a CA1 pyramidal neuron’s tolerance for input asynchrony by at last an order of magnitude. Therefore, it is shown using this model, that the time window for nonlinear integration is extended by more than an order of magnitude when inputs are short bursts as opposed to single spikes.
Reference:
1 . Gómez González JF, Mel BW, Poirazi P (2011) Distinguishing Linear vs. Non-Linear Integration in CA1 Radial Oblique Dendrites: It's about Time. Front Comput Neurosci 5:44 [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): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,p; I CAN; I Sodium; I Calcium; I Potassium; I_AHP;
Gap Junctions:
Receptor(s): NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Active Dendrites; Detailed Neuronal Models; Synaptic Integration;
Implementer(s):
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; NMDA; I Na,p; I CAN; I Sodium; I Calcium; I Potassium; I_AHP;
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CA1_Gomez_2011
mechanism
x86_64
ampa.mod *
cad.mod
cal.mod
calH.mod
can.mod *
car.mod
cat.mod
d3.mod *
gabaa.mod *
gabab.mod
h.mod
hha_old.mod
hha2.mod
ican.mod
ipulse1.mod *
ipulse2.mod *
kadist.mod
kaprox.mod
kca.mod
kct.mod
KdBG.mod
km.mod
nap.mod *
netstim.mod *
netstimmm.mod *
nmda.mod *
NMDAb.mod
somacar.mod
                            
TITLE HH channel that includes both a sodium and a delayed rectifier channel 
: and accounts for sodium conductance attenuation
: Bartlett Mel-modified Hodgkin - Huxley conductances (after Ojvind et al.)
: Terrence Brannon-added attenuation 
: Yiota Poirazi-modified Kdr and Na threshold and time constants
: to make it more stable, 2000, poirazi@LNC.usc.edu
: Used in all BUT somatic and axon sections. The spike threshold is about -50 mV
:
: Modified to use CVode --Carl Gold 08/12/03
:  Updated by Maria Markaki  12/05/03

NEURON {
	SUFFIX hha_old
	USEION na READ ena WRITE ina 
	USEION k READ ek WRITE ik
	NONSPECIFIC_CURRENT il
	RANGE gnabar, gkbar, gl, el
	RANGE ar2, vhalfs
	GLOBAL inf, tau, taumin
	RANGE W
}

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

PARAMETER {   : parameters that can be entered when function is called in cell-setup
        a0r = 0.0003 (/ms)
        b0r = 0.0003 (/ms)
        zetar = 12    
	zetas = 12   
        gmr = 0.2   
	ar2 = 1.0               :initialized parameter for location-dependent
                                :Na-conductance attenuation, "s", (ar=1 -> zero attenuation)
:	taumin = 10   (ms)       :min activation time for "s" attenuation system
	taumin = 3   (ms)       :min activation time for "s" attenuation system
        vvs  = 2     (mV)       :slope for "s" attenuation system
        vhalfr = -60 (mV)       :half potential for "s" attenuation system
        vvh=-58		(mV) 
	W = 0.016    (/mV)      :this 1/61.5 mV
:	gnabar = 0.2 (mho/cm2)  :suggested conductance values
:	gkbar = 0.12 (mho/cm2)
:	gl = 0.0001  (mho/cm2)
        gnabar = 0   (mho/cm2)  :initialized conductances
	gkbar = 0    (mho/cm2)  :actual values set in cell-setup.hoc
	gl = 0       (mho/cm2)
	el = -70.0   (mV)       :steady state 
}

STATE {                         : the unknown parameters to be solved in the DEs
	m h n s
}

ASSIGNED {			: parameters needed to solve DE
	celsius      (degC)
	v            (mV)
	ena          (mV)       :Na reversal potential (also reset in
	ek           (mV)       :K reversal potential  cell-setup.hoc)
	ina (mA/cm2)
	ik (mA/cm2)
	il (mA/cm2)
	inf[4]
	tau[4]		(ms)
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	ina = gnabar*m*m*h*s*(v - ena) :Sodium current
	ik = gkbar*n*n*(v - ek)        :Potassium current
	il = gl*(v - el)               :leak current
}

INITIAL {                       : initialize the following parameter using states()
	rates(v,ar2)
	m = inf[0]
	h = inf[1]
	n = inf[2]
	s = inf[3]
}

DERIVATIVE states {
	rates(v,ar2)
	m' = (inf[0]-m)/tau[0]
	h' = (inf[1]-h)/tau[1]
	n' = (inf[2]-n)/tau[2]
	s' = (inf[3]-s)/tau[3]
}


PROCEDURE rates(v(mV),a2) {
	LOCAL tmp, c
	FROM i=0 TO 2 {
		tau[i] = vartau(v,i)
		inf[i] = varss(v,i)
	}
	tau[3] = betr(v)/(a0r*(1+alpr(v))) 
	if (tau[3]<taumin) {tau[3]=taumin} :s activation tau
	c = alpv(v)
	inf[3] = c+a2*(1-c) 
}

FUNCTION varss(v(mV), i) { :steady state values
	if (i==0) {
	 	varss = 1 / (1 + exp((v + 40)/(-3(mV)))) :initial Na activation
	:	varss = 1 / (1 + exp((v + 44)/(-3(mV)))) :somatic value
	}
	else if (i==1) {
		varss = 1 / (1 + exp((v + 45)/(3(mV))))  :Na inactivation
	:	varss = 1 / (1 + exp((v + 45)/(3(mV))))  :initial value 
	:	varss = 1 / (1 + exp((v + 49)/(3.5(mV))))  :somatic Na inactivation
	}
	else if (i==2) {	
		varss = 1 / (1 + exp((v + 42)/(-2(mV)))) :K activation

	} 
}


FUNCTION alpv(v(mV)) {
         alpv = 1/(1+exp((v-vvh)/vvs))
}

FUNCTION alpr(v(mV)) {       :used in "s" activation system tau
UNITSOFF
  alpr = exp(1.e-3*zetar*(v-vhalfr)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION betr(v(mV)) {       :used in "s" activation system tau
UNITSOFF
  betr = exp(1.e-3*zetar*gmr*(v-vhalfr)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION vartau(v(mV), i) (ms){ :estimate tau values
	LOCAL tmp
	if (i==0) {
	   vartau = 0.05(ms)      :Na activation tau
	}
	else if (i==1) {
           vartau = 0.5(ms)       :Na inactivation tau
        }
	else if (i==2) {
            vartau = 2.2(ms)      :K activation tau
       	} 
}	

















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