Using Strahler's analysis to reduce realistic models (Marasco et al, 2013)

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Accession:149000
Building on our previous work (Marasco et al., (2012)), we present a general reduction method based on Strahler's analysis of neuron morphologies. We show that, without any fitting or tuning procedures, it is possible to map any morphologically and biophysically accurate neuron model into an equivalent reduced version. Using this method for Purkinje cells, we demonstrate how run times can be reduced up to 200-fold, while accurately taking into account the effects of arbitrarily located and activated synaptic inputs.
Reference:
1 . Marasco A, Limongiello A, Migliore M (2013) Using Strahler's analysis to reduce up to 200-fold the run time of realistic neuron models. Sci Rep 3:2934 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Dendrite;
Brain Region(s)/Organism: Hippocampus; Cerebellum;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Cerebellum Purkinje GABA cell;
Channel(s): I Na,t; I T low threshold; I K; I Calcium; Ca pump;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Action Potentials; Synaptic Integration;
Implementer(s): Limongiello, Alessandro [alessandro.limongiello at unina.it];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; Cerebellum Purkinje GABA cell; AMPA; I Na,t; I T low threshold; I K; I Calcium; Ca pump; Glutamate;
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PurkReductionOnLine
morphologies
readme.txt
CaE.mod *
CalciumP.mod *
CaP.mod *
CaP2.mod *
CaT.mod *
K2.mod *
K22.mod *
K23.mod *
KA.mod *
KC.mod *
KC2.mod *
KC3.mod *
KD.mod *
Kdr.mod *
Kh.mod *
Khh.mod *
KM.mod *
Leak.mod *
NaF.mod *
NaP.mod *
pj.mod
clusterisingMethods.hoc
fixnseg.hoc
mergingMethods.hoc
mosinit.hoc
ranstream.hoc *
RedPurk.hoc
stimulation1.hoc
useful&InitProc.hoc
                            
TITLE Fast sodium current
 
COMMENT
  from "An Active Membrane Model of the Cerebellar Purkinje Cell
        1. Simulation of Current Clamp in Slice"
ENDCOMMENT
 
UNITS {
        (mA) = (milliamp)
        (mV) = (millivolt)
}
 
NEURON {
        SUFFIX NaF
	USEION na WRITE ina
        RANGE  gnabar, gna, minf, hinf, mexp, hexp
} 
 
INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}
 
PARAMETER {
        v (mV)
        celsius = 37 (degC)
        dt (ms)
        gnabar	= 7.5 (mho/cm2)
        ena	= 45 (mV)

}
 
STATE {
        m h
}
 
ASSIGNED {
        ina (mA/cm2)
        gna minf hinf mexp hexp 
}
 
BREAKPOINT {
        SOLVE states
        gna = gnabar *m*m* m*h 
	ina = gna* (v-ena)
}
 
UNITSOFF
 
INITIAL {
	rates(v)
	m = minf
	h = hinf
}

PROCEDURE states() {  :Computes state variables m, h
        rates(v)      :             at the current v and dt.
        m = m + mexp*(minf-m)
        h = h + hexp*(hinf-h)
}
 
PROCEDURE rates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
        LOCAL  q10, tinc, alpha, beta, sum
        TABLE minf, mexp, hinf, hexp DEPEND dt, celsius FROM -100 TO 100 WITH 200
        q10 = 3^((celsius - 37)/10)
        tinc = -dt * q10
                :"m" sodium activation system
        alpha = 35/exp((v+5)/(-10))
        beta =  7/exp((v+65)/20)
        sum = alpha + beta
        minf = alpha/sum
        mexp = 1 - exp(tinc*sum)
                :"h" sodium inactivation system
        alpha = 0.225/(1+exp((v+80)/10))
        beta = 7.5/exp((v-3)/(-18))
        sum = alpha + beta
        hinf = alpha/sum
        hexp = 1 - exp(tinc*sum)
}

 
UNITSON


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