Discharge hysteresis in motoneurons (Powers & Heckman 2015)

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Accession:183949
"Motoneuron activity is strongly influenced by the activation of persistent inward currents (PICs) mediated by voltage-gated sodium and calcium channels. ... It has recently been suggested that a number of factors other than PIC can contribute to delta F (firing rate differences between motoneurons) values, including mechanisms underlying spike frequency adaptation and spike threshold accommodation. In the present study, we used a set of compartmental models representing a sample of 20 motoneurons with a range of thresholds to investigate how several different intrinsic motoneuron properties can potentially contribute to variations in F values. ... Our results indicate that, although other factors can contribute, variations in discharge hysteresis and delta F values primarily reflect the contribution of dendritic PICs to motoneuron activation.
Reference:
1 . Powers RK, Heckman CJ (2015) Contribution of intrinsic motoneuron properties to discharge hysteresis and its estimation based on paired motor unit recordings. A simulation study. J Neurophysiol 114:184-198 [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): Spinal cord lumbar motor neuron alpha cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I K; I M; I K,Ca; I_AHP; I Calcium; I Sodium;
Gap Junctions:
Receptor(s):
Gene(s): Kv1.2 KCNA2; Kv1.9 Kv7.1 KCNQ1;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Spike Frequency Adaptation;
Implementer(s): Powers, Randy [rkpowers at u.washington.edu];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha cell; I Na,p; I Na,t; I L high threshold; I K; I M; I K,Ca; I Sodium; I Calcium; I_AHP;
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Discharge_hysteresis
Model hoc files and output
README.txt
Gfluctdv.mod *
ghchan.mod *
kca2.mod *
KCNQ.mod *
kdrRL.mod *
km_hu.mod
kv1_gp.mod *
L_Ca.mod *
L_Ca_inact.mod *
mAHP.mod *
mAHPvt.mod
na3rp.mod *
naps.mod *
napsi.mod *
AHPlen.csv
FasterMis.csv
FR3cablepas.hoc
FRMot3dendNaHH.hoc
gramp.ses
HiDKCa.csv
init_3dend_gramp.hoc
LCai.csv
Napi.csv
pars2manyhocs.py *
ProxCa.csv
SetConductances2.hoc *
SlowM.csv
standard.csv
twobirampsdel.hoc *
                            
TITLE Motoneuron L-type Calcium channels
:
: The parameters for this current come from V. Booth et al. J Neurophysiol 78:3371-3385, 1997
: Iterative equations
: Modified by RP to provide calcium to a separate pool (caL)and to have adjustable equilibrium
: potential vca


NEURON {
	SUFFIX L_Ca_inact
	USEION caL READ ecaL WRITE icaL VALENCE 2
	RANGE gcabar,icaL,m_inf,m,h
	GLOBAL vca,theta_m,kappa_m,theta_h,kappa_h
}


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

PARAMETER {
	gcabar  = 0.0003  (mho/cm2)
	ecaL		(mV)	: eca can't be set here, only in hoc
:	celcius = 36	(degC)
	dt		(ms)
	tau_m	= 20	(ms)
	v		(mV)
        vca=80		(mV)
	theta_m = -30   (mV)
	kappa_m = -6	(-mV)
	tau_h	= 1500	(ms)
	theta_h = 14   (mV)
	kappa_h = 4	(-mV)
}

STATE {
	m
	h
}

ASSIGNED {
	icaL		(mA/cm2)
	m_inf
	h_inf
	tadj
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	icaL = gcabar * m *h* (v - vca)  :I have tried this as m*m also
}

DERIVATIVE states {
	evaluate_fct(v)
	m' = (m_inf - m) / tau_m
	h' = (h_inf - h) / tau_h
}

UNITSOFF
INITIAL {

:
:  Q10 was assumed to be 3 for both currents
:
:	tadj = 3.0 ^ ((celsius-36)/ 10 )

	evaluate_fct(v)
	m = m_inf
	h = h_inf
}

PROCEDURE evaluate_fct(v(mV)) {

	m_inf = 1 / (1 + (Exp((v - theta_m)/ kappa_m))): / tadj
	h_inf = 1 / (1 + (Exp((v - theta_h)/ kappa_h))): / tadj

}

FUNCTION vtrap(x,y) {
	if (fabs(x/y) < 1e-6) {
		vtrap = y*(1 - x/y/2)
	}else{
		vtrap = x/(Exp(x/y)-1)
	}
}

FUNCTION Exp(x) {
	if (x < -100) {
		Exp = 0
	}else{
		Exp = exp(x)
	}
} 


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