Excitability of PFC Basal Dendrites (Acker and Antic 2009)

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Accession:117207
".. We carried out multi-site voltage-sensitive dye imaging of membrane potential transients from thin basal branches of prefrontal cortical pyramidal neurons before and after application of channel blockers. We found that backpropagating action potentials (bAPs) are predominantly controlled by voltage-gated sodium and A-type potassium channels. In contrast, pharmacologically blocking the delayed rectifier potassium, voltage-gated calcium or Ih, conductance had little effect on dendritic action potential propagation. Optically recorded bAP waveforms were quantified and multicompartmental modeling (NEURON) was used to link the observed behavior with the underlying biophysical properties. The best-fit model included a non-uniform sodium channel distribution with decreasing conductance with distance from the soma, together with a non-uniform (increasing) A-type potassium conductance. AP amplitudes decline with distance in this model, but to a lesser extent than previously thought. We used this model to explore the mechanisms underlying two sets of published data involving high frequency trains of action potentials, and the local generation of sodium spikelets. ..."
Reference:
1 . Acker CD, Antic SD (2009) Quantitative assessment of the distributions of membrane conductances involved in action potential backpropagation along basal dendrites. J Neurophysiol 101:1524-41 [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: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Dendritic Action Potentials; Parameter Fitting; Active Dendrites; Detailed Neuronal Models; Calcium dynamics;
Implementer(s): Acker, Corey [acker at uchc.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I Potassium;
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acker_antic
Model
ca.mod *
Cad.mod
CaT.mod
IL.mod
kadist.mod
kaprox.mod *
kv.mod *
na.mod
PlateauConductance.mod
vmax.mod *
CA 229.hoc
PFC_L5Pyramid_AckerAntic06.hoc
                            
COMMENT
T-type Ca channel 
ca.mod to lead to thalamic ca current inspired by destexhe and huguenrd
Uses fixed eca instead of GHK eqn
changed from (AS Oct0899)
changed for use with Ri18  (B.Kampa 2005)

added DERIVATIVE block for use with cvode (C.Acker 2008)
ENDCOMMENT

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	SUFFIX it
	USEION ca READ eca WRITE ica
	RANGE m, h, gca, gbar
	RANGE minf, hinf, mtau, htau, inactF, actF
	GLOBAL  vshift,vmin,vmax, v12m, v12h, vwm, vwh, am, ah, vm1, vm2, vh1, vh2, wm1, wm2, wh1, wh2
}

PARAMETER {
	gbar = 0.0008 (mho/cm2)	: 0.12 mho/cm2
	vshift = 0	(mV)		: voltage shift (affects all)

	cao  = 2.5	(mM)	        : external ca concentration
	cai		(mM)
						 
	v 		(mV)
	dt		(ms)
	celsius		(degC)
	vmin = -120	(mV)
	vmax = 100	(mV)

	v12m=50         	(mV)
	v12h=78         	(mV)
	vwm =7.4         	(mV)
	vwh=5.0         	(mV)
	am=3         	(mV)
	ah=85         	(mV)
	vm1=25         	(mV)
	vm2=100         	(mV)
	vh1=46         	(mV)
	vh2=405         	(mV)
	wm1=20         	(mV)
	wm2=15         	(mV)
	wh1=4         	(mV)
	wh2=50         	(mV)


}


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)
	FARADAY = (faraday) (coulomb)
	R = (k-mole) (joule/degC)
	PI	= (pi) (1)
} 

ASSIGNED {
	ica 		(mA/cm2)
	gca		(pS/um2)
	eca		(mV)
	minf 		hinf
	mtau (ms)	htau (ms)
	tadj
}
 

STATE { m h }

INITIAL { 
	trates(v+vshift)
	m = minf
	h = hinf
}

BREAKPOINT {
   SOLVE states METHOD cnexp
   gca = gbar*m*m*h
   ica = gca * (v - eca)
} 

DERIVATIVE states {
   trates(v+vshift)      
   m' =  (minf-m)/mtau
   h' =  (hinf-h)/htau
}

PROCEDURE trates(v) {  
   TABLE minf, hinf, mtau, htau
   FROM vmin TO vmax WITH 199
   
   rates(v): not consistently executed from here if usetable == 1

}


PROCEDURE rates(v_) {  
   LOCAL  a, b

   minf = 1.0 / ( 1 + exp(-(v_+v12m)/vwm) )
   hinf = 1.0 / ( 1 + exp((v_+v12h)/vwh) )

   mtau = ( am + 1.0 / ( exp((v_+vm1)/wm1) + exp(-(v_+vm2)/wm2) ) ) 
   htau = ( ah + 1.0 / ( exp((v_+vh1)/wh1) + exp(-(v_+vh2)/wh2) ) ) 
}


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