Alcohol action in a detailed Purkinje neuron model and an efficient simplified model (Forrest 2015)

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Accession:180789
" ... we employ a novel reduction algorithm to produce a 2 compartment model of the cerebellar Purkinje neuron from a previously published, 1089 compartment model. It runs more than 400 times faster and retains the electrical behavior of the full model. So, it is more suitable for inclusion in large network models, where computational power is a limiting issue. We show the utility of this reduced model by demonstrating that it can replicate the full model’s response to alcohol, which can in turn reproduce experimental recordings from Purkinje neurons following alcohol application. ..."
Reference:
1 . Forrest MD (2015) Simulation of alcohol action upon a detailed Purkinje neuron model and a simpler surrogate model that runs >400 times faster. BMC Neurosci 16:27 [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: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s): I Na,t; I T low threshold; I A; I K; I K,leak; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow; I_HERG; Na/Ca exchanger; Na/K pump; I_AHP; I Cl, leak; I Na, leak; I Ca,p; I_KD; Ca pump;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Dendritic Action Potentials; Bursting; Ion Channel Kinetics; Oscillations; Simplified Models; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Sodium pump; Depolarization block; Dendritic Bistability; Markov-type model; Alcohol Use Disorder;
Implementer(s): Forrest, Michael [mikeforrest at hotmail.com];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; I Na,t; I T low threshold; I A; I K; I K,leak; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium; I A, slow; I_HERG; Na/Ca exchanger; Na/K pump; I_AHP; I Cl, leak; I Na, leak; I Ca,p; I_KD; Ca pump;
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Forrest2015
collapse_algorithm
README.txt
bkpkj.mod *
cad.mod *
cadiff.mod *
cae.mod *
cap2.mod *
captain.mod *
cat.mod *
cha.mod *
erg.mod *
gkca.mod *
hpkj.mod *
k23.mod *
ka.mod *
kc3.mod *
kd.mod *
kdyn.mod *
khh.mod *
km.mod *
kpkj.mod *
kpkj2.mod *
kpkjslow.mod *
kv1.mod *
leak.mod *
lkpkj.mod *
myexchanger.mod *
myexchangersoma.mod *
mypump.mod *
mypumpsoma.mod *
nadifl.mod *
narsg.mod *
newnew.mod *
pump.mod *
2_compartment.hoc
full.ses *
full_data_writer.hoc
full_morph.hoc
lesbos.ses *
mex.hoc
mosinit.hoc
mosinit_full.hoc
mosinit_simple.hoc
simple_data_writer.hoc
                            
TITLE gsquid.mod   squid potassium channel
: FORREST MD (2014) Two Compartment Model of the Cerebellar Purkinje Neuron
 
COMMENT
 This is the original Hodgkin-Huxley treatment for the set of sodium, 
  potassium, and leakage channels found in the squid giant axon membrane.
  ("A quantitative description of membrane current and its application 
  conduction and excitation in nerve" J.Physiol. (Lond.) 117:500-544 (1952).)
 Membrane voltage is in absolute mV and has been reversed in polarity
  from the original HH convention and shifted to reflect a resting potential
  of -65 mV.
 Initialize this mechanism to steady-state voltage by calling
  rates_gsquid(v) from HOC, then setting m_gsquid=minf_gsquid, etc.
 Remember to set celsius=6.3 (or whatever) in your HOC file.
 See hh1.hoc for an example of a simulation using this model.
 SW Jaslove  6 March, 1992
ENDCOMMENT
 
UNITS {
        (mA) = (milliamp)
        (mV) = (millivolt)
}
 
NEURON {
        SUFFIX khh
        USEION k READ ek WRITE ik
        RANGE   gk,  gkbar, ik
        GLOBAL  ninf, nexp
}
 
INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}
 
PARAMETER {
        v (mV)
        celsius = 37 (degC)
        dt (ms)
        gkbar = .036 (mho/cm2)
     :   ek = -85(mV)
}
 
STATE {
         n
}
 
ASSIGNED {
        ik (mA/cm2)
        gk ninf nexp
         ek (mV)
}
 
BREAKPOINT {
        SOLVE states
        gk  = gkbar*n*n*n*n

        ik = gk*(v - ek)      
}
 
UNITSOFF
 
INITIAL {
	rates(v)
	n = ninf
}

PROCEDURE states() {  :Computes state variable n 
        rates(v)      :             at the current v and dt.
        n = n + nexp*(ninf-n)
}
 
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 ninf, nexp DEPEND dt, celsius FROM -100 TO 100 WITH 200
        q10 = 3^((celsius - 37)/10)
        tinc = -dt * q10
                :"n" potassium activation system
        alpha = .01*vtrap(-(v+55),10) 
        beta = .125*exp(-(v+65)/80)
        sum = alpha + beta
        ninf = alpha/sum
        nexp = 1 - exp(tinc*sum)
}

FUNCTION vtrap(x,y) {  :Traps for 0 in denominator of rate eqns.
        if (fabs(x/y) < 1e-6) {
                vtrap = y*(1 - x/y/2)
        }else{
                vtrap = x/(exp(x/y) - 1)
        }
}
 
UNITSON


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