Altered complexity in layer 2/3 pyramidal neurons (Luuk van der Velden et al. 2012)

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Accession:147514
" ... Our experimental results show that hypercomplexity of the apical dendritic tuft of layer 2/3 pyramidal neurons affects neuronal excitability by reducing the amount of spike frequency adaptation. This difference in firing pattern, related to a higher dendritic complexity, was accompanied by an altered development of the afterhyperpolarization slope with successive action potentials. Our abstract and realistic neuronal models, which allowed manipulation of the dendritic complexity, showed similar effects on neuronal excitability and confirmed the impact of apical dendritic complexity. Alterations of dendritic complexity, as observed in several pathological conditions such as neurodegenerative diseases or neurodevelopmental disorders, may thus not only affect the input to layer 2/3 pyramidal neurons but also shape their firing pattern and consequently alter the information processing in the cortex."
Reference:
1 . van der Velden L, van Hooft JA, Chameau P (2012) Altered dendritic complexity affects firing properties of cortical layer 2/3 pyramidal neurons in mice lacking the 5-HT3A receptor. J Neurophysiol 108:1521-8 [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): Neocortex spiking regular (RS) neuron;
Channel(s): Ca pump;
Gap Junctions:
Receptor(s): 5-HT3;
Gene(s):
Transmitter(s): Serotonin;
Simulation Environment: NEURON;
Model Concept(s): Influence of Dendritic Geometry;
Implementer(s): van der Velden, Luuk [l.j.j.vandervelden at uva.nl];
Search NeuronDB for information about:  5-HT3; Ca pump; Serotonin;
/
dendritic_complexity
README.html
ca.mod *
cad.mod *
cadif.mod
cadif_pump.mod
kca.mod *
km.mod *
kv.mod *
L_HVA_Ca.mod *
na.mod
altered_complexity_model.hoc
mosinit.hoc
screenshot.png
                            
TITLE Motoneuron HVA L-type Calcium channels
:
: The parameters for this current come from V. Booth et al. J Neurophysiol 78:3371-3385, 1997
: Iterative equations
:	I shifted the activation of this current to the same range as N_Ca.mod 
:



NEURON {
	SUFFIX L_HVA_Ca
	USEION ca READ eca WRITE ica
	RANGE gcabar
	RANGE m_inf
}


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

PARAMETER {
	gcabar  = 0.0003 (mho/cm2)  :original = 7e-05
	eca	= 80	(mV)
:	celcius = 36	(degC)
	dt		(ms)
	tau_m	= 20	(ms)
	v		(mV)
	theta_m = -10	(mV)
	kappa_m = -6    (mV)	:original = -7
}

STATE {
	m 
}

ASSIGNED {
	ica		(mA/cm2)
	m_inf
	tadj
}

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

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

UNITSOFF
INITIAL {

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

	evaluate_fct(v)
	m = m_inf
}

PROCEDURE evaluate_fct(v(mV)) {

	m_inf = 1 / (1 + (Exp((v - theta_m)/ kappa_m))): / 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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