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

 Download zip file   Auto-launch 
Help downloading and running models
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. 108:1521-1528 [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
                            
COMMENT
26 Ago 2002 Modification of original channel to allow variable time step and to correct an initialization error.
    Done by Michael Hines(michael.hines@yale.e) and Ruggero Scorcioni(rscorcio@gmu.edu) at EU Advance Course in Computational Neuroscience. Obidos, Portugal

ca.mod
Uses fixed eca instead of GHK eqn

HVA Ca current
Based on Reuveni, Friedman, Amitai and Gutnick (1993) J. Neurosci. 13:
4609-4621.

Author: Zach Mainen, Salk Institute, 1994, zach@salk.edu

ENDCOMMENT

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

NEURON {
	SUFFIX ca
	USEION ca READ eca WRITE ica
	RANGE m, h, gca, gbar
	RANGE minf, hinf, mtau, htau
	GLOBAL q10, temp, tadj, vmin, vmax, vshift
}

PARAMETER {
	gbar = 0.1   	(pS/um2)	: 0.12 mho/cm2
	vshift = 0	(mV)		: voltage shift (affects all)

	cao  = 2.5	(mM)	        : external ca concentration
	cai		(mM)
						
	temp = 23	(degC)		: original temp 
	q10  = 2.3			: temperature sensitivity

	v 		(mV)
	dt		(ms)
	celsius		(degC)
	vmin = -120	(mV)
	vmax = 100	(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 = tadj*gbar*m*m*h
	ica = (1e-4) * gca * (v - eca)
} 

LOCAL mexp, hexp

:PROCEDURE states() {
:        trates(v+vshift)      
:        m = m + mexp*(minf-m)
:        h = h + hexp*(hinf-h)
:	VERBATIM
:	return 0;
:	ENDVERBATIM
:}

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

PROCEDURE trates(v) {  
                      
        
        TABLE minf, hinf, mtau, htau 
	DEPEND  celsius, temp
	
	FROM vmin TO vmax WITH 199

	rates(v): not consistently executed from here if usetable == 1

:        tinc = -dt * tadj

:        mexp = 1 - exp(tinc/mtau)
:        hexp = 1 - exp(tinc/htau)
}


PROCEDURE rates(vm) {  
        LOCAL  a, b

        tadj = q10^((celsius - temp)/10)

	a = 0.055*(-27 - vm)/(exp((-27-vm)/3.8) - 1)
	b = 0.94*exp((-75-vm)/17)
	
	mtau = 1/tadj/(a+b)
	minf = a/(a+b)

		:"h" inactivation 

	a = 0.000457*exp((-13-vm)/50)
	b = 0.0065/(exp((-vm-15)/28) + 1)

	htau = 1/tadj/(a+b)
	hinf = a/(a+b)
}

FUNCTION efun(z) {
	if (fabs(z) < 1e-4) {
		efun = 1 - z/2
	}else{
		efun = z/(exp(z) - 1)
	}
}

Loading data, please wait...