2D model of olfactory bulb gamma oscillations (Li and Cleland 2017)

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Accession:232097
This is a biophysical model of the olfactory bulb (OB) that contains three types of neurons: mitral cells, granule cells and periglomerular cells. The model is used to study the cellular and synaptic mechanisms of OB gamma oscillations. We concluded that OB gamma oscillations can be best modeled by the coupled oscillator architecture termed pyramidal resonance inhibition network gamma (PRING).
Reference:
1 . Li G, Cleland TA (2017) A coupled-oscillator model of olfactory bulb gamma oscillations PLOS Computational Biology 13(11):e1005760 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Olfactory bulb main mitral cell; Olfactory bulb main interneuron granule MC cell; Olfactory bulb main interneuron periglomerular cell;
Channel(s):
Gap Junctions:
Receptor(s): AMPA; NMDA; GabaA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Li, Guoshi [guoshi_li at med.unc.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral cell; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell; GabaA; AMPA; NMDA;
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OBGAMMA
celldata
connection
data0
input
README
cadecay.mod *
cadecay2.mod *
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Can.mod *
CaPN.mod *
CaT.mod *
GradeAMPA.mod *
GradeGABA.mod *
GradNMDA.mod *
hpg.mod *
kAmt.mod *
KCa.mod *
KDRmt.mod *
kfasttab.mod *
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KS.mod
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LCa.mod *
nafast.mod *
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Nicotin.mod *
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OdorInput.mod *
SineInput.mod
Background.hoc
Cal_Synch.hoc
Connect.hoc
Figure.hoc
GC_def.hoc
GC_save.hoc *
GC_Stim.hoc
Input.hoc
mathslib.hoc
MC_def.hoc
MC_save.hoc
MC_Stim.hoc
mosinit.hoc
OBNet.hoc
Parameter.hoc
PG_def.hoc
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PG_Stim.hoc
SaveData.hoc
tabchannels.dat *
tabchannels.hoc
                            
: $Id: fvpre.mod,v 1.10 2003/07/29 23:37:22 billl Exp $
COMMENT
synapse taken from Wang, X.-J. and Buzsaki G. (1996) Gamma oscillations by
synaptic inhibition in a hippocampal interneuronal network.  
J. Neurosci. 16, 6402-6413.
ENDCOMMENT
					       
NEURON {
  POINT_PROCESS gradGABA
  RANGE gmax, g, i, alpha, beta, thetasyn,e, sigma
  :GLOBAL thetasyn,e
  NONSPECIFIC_CURRENT i
  POINTER vpre
}

UNITS {
  (nA) = (nanoamp)
  (mV) = (millivolt)
  (uS) = (microsiemens)
}

PARAMETER {
  gmax  = 1e-3 (uS)
  alpha = 0.8 (/ms)    : 1.25 ms
  beta  = 0.0556 (/ms) : 18 ms
  e = -80	  (mV)     : Reserval potential
  thetasyn = -40 (mV)  : Activation threshold
  sigma    =  2
}

ASSIGNED { vpre (mV) v (mV) i (nA)  g (uS)}

STATE { s }

INITIAL {
  s =  alpha*F(vpre)/(alpha*F(vpre)+beta)
}

BREAKPOINT {
  SOLVE state METHOD cnexp
  g = gmax * s
  i = g*(v - e)
}

DERIVATIVE state {
  s' = alpha*F(vpre)*(1-s) - beta*s
}

FUNCTION F (v1 (mV)) {
  F = 1/(1 + exp(-(v1-thetasyn)/sigma))
}  

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