Olfactory bulb mitral cell gap junction NN model: burst firing and synchrony (O`Connor et al. 2012)

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Accession:146030
In a network of 6 mitral cells connected by gap junction in the apical dendrite tuft, continuous current injections of 0.06 nA are injected into 20 locations in the apical tufts of two of the mitral cells. The current injections into one of the cells starts 10 ms after the other to generate asynchronous firing in the cells (Migliore et al. 2005 protocol). Firing of the cells is asynchronous for the first 120 ms. However after the burst firing phase is completed the firing in all cells becomes synchronous.
Reference:
1 . O'Connor S, Angelo K, Jacob TJC (2012) Burst firing versus synchrony in a gap junction connected olfactory bulb mitral cell network model. 6:75. Frontiers in Computational Neuroscience 6:75:1-18
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral GLU cell;
Channel(s): I Na,t; I L high threshold; I A; I K; I K,Ca;
Gap Junctions: Gap junctions;
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Bursting; Oscillations; Synchronization; Active Dendrites; Influence of Dendritic Geometry; Calcium dynamics; Olfaction;
Implementer(s):
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; I Na,t; I L high threshold; I A; I K; I K,Ca;
/
oconnoretal2012
README
AMPA.mod
Ca_mit_conc_ChannelML.mod
CurrentClampExt.mod
KA_ChannelML.mod
KCa3_ChannelML_new.mod
Kdr_ChannelML.mod
LCa3_mit_usb_ChannelML.mod
LeakConductance.mod
NaxSH0_ChannelML.mod
NaxSH10_ChannelML.mod
SynForRndSpike.mod
Cell1.hoc
Cell2.hoc
Cell3.hoc
Cell4.hoc
Cell5.hoc
Cell6.hoc
cellCheck.hoc
CellPositions.dat
ElectricalInputs.dat
gap.hoc
init.hoc
mosinit.hoc *
nCtools.hoc
NetworkConnections.dat
regenerateMods
simulation.props
                            
COMMENT

   **************************************************
   File generated by: neuroConstruct v1.3.8 
   **************************************************

   This file holds the implementation in NEURON of the Cell Mechanism:
   LCa3_mit_usb_ChannelML (Type: Channel mechanism, Model: ChannelML based process)

   with parameters: 
   /channelml/@units = SI Units 
   /channelml/notes = ChannelML file containing a single Channel description 
   /channelml/ion/@name = ca 
   /channelml/ion/@charge = 2 
   /channelml/ion/@default_erev = 0.070 
   /channelml/channel_type/@name = LCa3_mit_usb_ChannelML 
   /channelml/channel_type/@density = yes 
   /channelml/channel_type/status/@value = stable 
   /channelml/channel_type/status/comment = L channel data from: T. Hirano and S. Hagiwara Pflugers A 413(5) pp463-469, 1989 
   /channelml/channel_type/status/contributor/name = Simon O'Connor 
   /channelml/channel_type/notes = L type calcium conductance Hirano and Hagiwara 1989 
   /channelml/channel_type/authorList/modelTranslator/name = Simon O'Connor 
   /channelml/channel_type/authorList/modelTranslator/institution = University of Cardiff 
   /channelml/channel_type/authorList/modelTranslator/email = simon.oconnor@btinternet.com 
   /channelml/channel_type/publication/fullTitle = U. S. Bhalla and J. M. Bower, Exploring parameter space in detailed single neuron models: simulations of the mitral and granule cells of the olfactory ... 
   /channelml/channel_type/publication/pubmedRef = http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=7688798 
   /channelml/channel_type/neuronDBref/modelName = Na channels 
   /channelml/channel_type/neuronDBref/uri = http://senselab.med.yale.edu/senselab/NeuronDB/channelGene2.htm#table2 
   /channelml/channel_type/current_voltage_relation/ohmic/@ion = ca 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/@default_gmax = 120 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/gate[1]/@power = 1 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/gate[1]/state/@name = m 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/gate[1]/state/@fraction = 1 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/gate[2]/@power = 1 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/gate[2]/state/@name = h 
   /channelml/channel_type/current_voltage_relation/ohmic/conductance/gate[2]/state/@fraction = 1 
   /channelml/channel_type/hh_gate[1]/@state = m 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/@type = sigmoid 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/@expr = A/(1 + exp(k*(v-d))) 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/parameter[1]/@name = A 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/parameter[1]/@value = 7500 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/parameter[2]/@name = k 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/parameter[2]/@value = -142.85714285714286 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/parameter[3]/@name = d 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/alpha/parameterised_hh/parameter[3]/@value = 0.013 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/@type = sigmoid 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/@expr = A/(1 + exp(k*(v-d))) 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/parameter[1]/@name = A 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/parameter[1]/@value = 1650 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/parameter[2]/@name = k 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/parameter[2]/@value = 250 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/parameter[3]/@name = d 
   /channelml/channel_type/hh_gate[1]/transition/voltage_gate/beta/parameterised_hh/parameter[3]/@value = 0.014 
   /channelml/channel_type/hh_gate[2]/@state = h 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/@type = sigmoid 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/@expr = A/(1 + exp(k*(v-d))) 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/parameter[1]/@name = A 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/parameter[1]/@value = 6.800 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/parameter[2]/@name = k 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/parameter[2]/@value = 83.333333333333 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/parameter[3]/@name = d 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/alpha/parameterised_hh/parameter[3]/@value = -0.030 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/@type = sigmoid 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/@expr = A/(1 + exp(k*(v-d))) 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/parameter[1]/@name = A 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/parameter[1]/@value = 60 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/parameter[2]/@name = k 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/parameter[2]/@value = -90.90909090909 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/parameter[3]/@name = d 
   /channelml/channel_type/hh_gate[2]/transition/voltage_gate/beta/parameterised_hh/parameter[3]/@value = 0.0 
   /channelml/channel_type/impl_prefs/table_settings/@max_v = 0.05 
   /channelml/channel_type/impl_prefs/table_settings/@min_v = -0.1 
   /channelml/channel_type/impl_prefs/table_settings/@table_divisions = 3000 

// File from which this was generated: /home/Simon/nC_projects/Rat_Mitral_Cell_Gap_Network_copy4/cellMechanisms/LCa3_mit_usb_ChannelML/CaChannel.xml

// XSL file with mapping to simulator: /home/Simon/nC_projects/Rat_Mitral_Cell_Gap_Network_copy4/cellMechanisms/LCa3_mit_usb_ChannelML/ChannelML_v1.8.0_NEURONmod.xsl

ENDCOMMENT


?  This is a NEURON mod file generated from a ChannelML file

?  Unit system of original ChannelML file: SI Units

COMMENT
    ChannelML file containing a single Channel description
ENDCOMMENT

TITLE Channel: LCa3_mit_usb_ChannelML

COMMENT
    L type calcium conductance Hirano and Hagiwara 1989
ENDCOMMENT


UNITS {
    (mA) = (milliamp)
    (mV) = (millivolt)
    (S) = (siemens)
    (um) = (micrometer)
    (molar) = (1/liter)
    (mM) = (millimolar)
    (l) = (liter)
}


    
NEURON {
      

    SUFFIX LCa3_mit_usb_ChannelML
    USEION ca READ eca WRITE ica VALENCE 2 ? reversal potential of ion is read, outgoing current is written
            
    RANGE gmax, gion
    
    RANGE minf, mtau
    RANGE hinf, htau
}

PARAMETER { 
      

    gmax = 0.012 (S/cm2) ? default value, should be overwritten when conductance placed on cell
    
}



ASSIGNED {
      

    v (mV)
    
    celsius (degC)
    
    ? Reversal potential of ca
    eca (mV)
    ? The outward flow of ion: ca calculated by rate equations...
    ica (mA/cm2)
            
    
    gion (S/cm2)
    minf
    mtau (ms)
    hinf
    htau (ms)
    
}

BREAKPOINT { 
                        
    SOLVE states METHOD cnexp
         

    gion = gmax*((1*m)^1)*((1*h)^1)
    ica = gion*(v - eca)
                

}



INITIAL {
    eca = 70
        
    rates(v)
    m = minf
                
        
    h = hinf
                
        
    
    
}
    
STATE {
    m
    h
    
}

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

PROCEDURE rates(v(mV)) {  
    
    ? Note: not all of these may be used, depending on the form of rate equations
    LOCAL  alpha, beta, tau, inf, gamma, zeta, temp_adj_m, A_alpha_m, k_alpha_m, d_alpha_m, A_beta_m, k_beta_m, d_beta_m, temp_adj_h, A_alpha_h, k_alpha_h, d_alpha_h, A_beta_h, k_beta_h, d_beta_h
        
    TABLE minf, mtau,hinf, htau
 DEPEND celsius
 FROM -100 TO 50 WITH 3000
    
    
    UNITSOFF
    temp_adj_m = 1
    temp_adj_h = 1
    
        
    ?      ***  Adding rate equations for gate: m  ***
        
    ? Found a parameterised form of rate equation for alpha, using expression: A / (1 + exp(k*(v-d)))
    A_alpha_m = 7500
    k_alpha_m = -142.85714285714286
    d_alpha_m = 0.013
    
    ? Unit system in ChannelML file is SI units, therefore need to 
    ? convert these to NEURON quanities...
                        A_alpha_m = A_alpha_m * 0.0010   ? 1/ms
    k_alpha_m = k_alpha_m * 0.0010   ? mV
    d_alpha_m = d_alpha_m * 1000   ? mV
          
                     
    
    alpha = A_alpha_m / (exp((v - d_alpha_m) * k_alpha_m) + 1)
    
    
    ? Found a parameterised form of rate equation for beta, using expression: A / (1 + exp(k*(v-d)))
    A_beta_m = 1650
    k_beta_m = 250
    d_beta_m = 0.014
    
    ? Unit system in ChannelML file is SI units, therefore need to 
    ? convert these to NEURON quanities...
                        A_beta_m = A_beta_m * 0.0010   ? 1/ms
    k_beta_m = k_beta_m * 0.0010   ? mV
    d_beta_m = d_beta_m * 1000   ? mV
          
                     
    
    beta = A_beta_m / (exp((v - d_beta_m) * k_beta_m) + 1)
    
    mtau = 1/(temp_adj_m*(alpha + beta))
    minf = alpha/(alpha + beta)
          
       
    
    ?     *** Finished rate equations for gate: m ***
    
        
        
    ?      ***  Adding rate equations for gate: h  ***
        
    ? Found a parameterised form of rate equation for alpha, using expression: A / (1 + exp(k*(v-d)))
    A_alpha_h = 6.800
    k_alpha_h = 83.333333333333
    d_alpha_h = -0.030
    
    ? Unit system in ChannelML file is SI units, therefore need to 
    ? convert these to NEURON quanities...
                        A_alpha_h = A_alpha_h * 0.0010   ? 1/ms
    k_alpha_h = k_alpha_h * 0.0010   ? mV
    d_alpha_h = d_alpha_h * 1000   ? mV
          
                     
    
    alpha = A_alpha_h / (exp((v - d_alpha_h) * k_alpha_h) + 1)
    
    
    ? Found a parameterised form of rate equation for beta, using expression: A / (1 + exp(k*(v-d)))
    A_beta_h = 60
    k_beta_h = -90.90909090909
    d_beta_h = 0.0
    
    ? Unit system in ChannelML file is SI units, therefore need to 
    ? convert these to NEURON quanities...
                        A_beta_h = A_beta_h * 0.0010   ? 1/ms
    k_beta_h = k_beta_h * 0.0010   ? mV
    d_beta_h = d_beta_h * 1000   ? mV
          
                     
    
    beta = A_beta_h / (exp((v - d_beta_h) * k_beta_h) + 1)
    
    htau = 1/(temp_adj_h*(alpha + beta))
    hinf = alpha/(alpha + beta)
          
       
    
    ?     *** Finished rate equations for gate: h ***
    
             

}


UNITSON



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