Molecular layer interneurons in cerebellum encode valence in associative learning (Ma et al 2020)

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Accession:266578
We used two-photon microscopy to study the role of ensembles of cerebellar molecular layer interneurons (MLIs) in a go-no go task where mice obtain a sugar water reward. In order to begin understanding the circuit basis of our findings in changes in lick behavior with chemogenetics in the go-no go associative learning olfactory discrimination task we generated a simple computational model of MLI interaction with PCs.
Reference:
1 . Ma M, Futia GL, De Souza FM, Ozbay BN, Llano I, Gibson EA, Restrepo D (2020) Molecular layer interneurons in the cerebellum encode for valence in associative learning Nat Commun . [PubMed]
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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; Mouse;
Cell Type(s): Cerebellum Purkinje GABA cell; Cerebellum interneuron stellate GABA cell;
Channel(s):
Gap Junctions:
Receptor(s): AMPA; GabaA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; Detailed Neuronal Models;
Implementer(s): Simoes-de-Souza, Fabio [fabio.souza at ufabc.edu.br];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; Cerebellum interneuron stellate GABA cell; GabaA; AMPA; Gaba; Glutamate;
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MaEtAl2020
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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