Olfactory bulb microcircuits model with dual-layer inhibition (Gilra & Bhalla 2015)

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Accession:153574
A detailed network model of the dual-layer dendro-dendritic inhibitory microcircuits in the rat olfactory bulb comprising compartmental mitral, granule and PG cells developed by Aditya Gilra, Upinder S. Bhalla (2015). All cell morphologies and network connections are in NeuroML v1.8.0. PG and granule cell channels and synapses are also in NeuroML v1.8.0. Mitral cell channels and synapses are in native python.
Reference:
1 . Gilra A, Bhalla US (2015) Bulbar microcircuit model predicts connectivity and roles of interneurons in odor coding. PLoS One 10:e0098045 [PubMed]
Citations  Citation Browser
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; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell;
Channel(s): I A; I h; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: Python; MOOSE/PyMOOSE;
Model Concept(s): Sensory processing; Sensory coding; Markov-type model; Olfaction;
Implementer(s): Bhalla, Upinder S [bhalla at ncbs.res.in]; Gilra, Aditya [aditya_gilra -at- yahoo -period- com];
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell; AMPA; NMDA; Gaba; I A; I h; I K,Ca; I Sodium; I Calcium; I Potassium; Gaba; Glutamate;
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olfactory-bulb-gilra-bhalla
channels
neuron_channels
CaHVA_Chan.xml
CaL_Chan.xml
CaLChannel.py
CaPool.py
CaTChannel.py
channelConstants.py
granuleDefaults.py
Ih_cb.xml
KAChannel.py
KAChannelMS.py
KCaA.dat
KCaA_PG.dat
KCaB.dat
KCaB_PG.dat
KCaChannel.py
KCaChannel_PG.py
KCaMPIChannel.py
KCaMPIChannel_PG.py
KDRChannelMS.py
kfast_k.inf *
kfast_k.tau *
kfast_n.inf *
kfast_n.tau *
KFastChannel.py
KMChannel.py
kslow_k.inf *
kslow_k.tau *
kslow_n.inf *
kslow_n.tau *
KSlowChannel.py
load_channels.py
MOOSEChannelTest.py
NaChannel.py
NaGranChannel.py
NaMitChannelMS.py
tabchannels.dat *
TCa_d.xml
                            
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import math

# The PYTHONPATH should contain the location of moose.py and _moose.so
# files.  Putting ".." with the assumption that moose.py and _moose.so
# has been generated in ${MOOSE_SOURCE_DIRECTORY}/pymoose/ (as default
# pymoose build does) and this file is located in
# ${MOOSE_SOURCE_DIRECTORY}/pymoose/examples
# sys.path.append('..\..')
try:
    import moose
except ImportError:
    print "ERROR: Could not import moose. Please add the directory containing moose.py in your PYTHONPATH"
    import sys
    sys.exit(1)

from channelConstants import *

# This Na channel is the same for mitral and granule 'naxn.mod' in Migliore and Shepherd 2008,
# except for VNa and sh.
# sh and VNa are passed to the constructor

#VNa = 50e-3 # Volts # Migliore and Shepherd 2008 mitral - different from granule 60mV

GNa = 200*sarea # Siemens, from mit4.hoc and then multiplying by area of mitral soma

## Lifted directly from Migliore and Shepherd 2008 Na gran channel
#sh = 10e-3 # V # (5mV in nmdol but 10mV in hoc file - mitral.hoc) - 15mV for granule
mmin=0.02e-3 # s
hmin=0.5e-3 # s
qt = 2.0**((CELSIUS-24.0)/10.0) # CELSIUS is defined in globalConstants.py
#Na_alpha_m:
tha = -30e-3 #V
Ra=0.4e6 # /s/V,
qa=7.2e-3 #V
#Na_beta_m:
tha = -30e-3 #V
Rb=0.124e6 # /s/V
qa=7.2e-3 # V
#Na_alpha_h:
thi1 = -45e-3 #V
Rd=0.03e6 # /s/V
qd=1.5e-3 #V 
#Na_beta_h:
thi2 = -45e-3 #V
Rg=0.01e6 # /s/V
qg=1.5e-3 #V 
### They use the above to calculate minf, mtau, htau, BUT finally have a different formula for hinf!!!
thinf = -50e-3 #V
qinf = 4e-3 #V

def trap0(vminusth,a,q):
	if (abs(vminusth) > 1e-9):
	    return a * (vminusth) / (1 - math.exp(-(vminusth)/q))
	else:
	    return a * q

#### V IMP: 10^6 factor in alpha_m and beta_m, as there is V in Nr, so the constant in front had units ms-1 mV^-1, so the 10^6 factor.
#def calc_Na_alpha_m(v):
#    #return 0.32e6*(v+42e-3)/(1-math.exp(-(42e-3+v)/4e-3)) # From Bhalla and Bower 1993 paper
#    return 400.0*(v+15e-3)/(1-math.exp(-(15e-3+v)/7.2e-3)) # tha+sh=-15mV. Use 15mV instead of 42mV
#
#def calc_Na_beta_m(v):
#    #return 0.28e6*(v+15e-3)/(-1+math.exp((15e-3+v)/5e-3)) # From Bhalla and Bower 1993 paper
#    return 124.0*(v-15e-3)/(-1+math.exp((-15e-3+v)/7.2e-3)) # -tha-sh=15mV. Use -15mV instead of 15mV
#
#def calc_Na_alpha_h(v):
#    #return 0.128e3/math.exp((v+38e-3)/18e-3) # From Bhalla and Bower 1993 paper
#    return 30.0*(v+30e-3)/math.exp((v+30e-3)/1.5e-3) # thi1+sh = -30mV, Use 30mV instead of 38mV.
#
#def calc_Na_beta_h(v):
#    #return 4.0e3/(1+math.exp(-(v+15e-3)/5.0e-3)) # From Bhalla and Bower 1993 paper
#    return 10.0*(v-30e-3)/(1+math.exp(-(v-30e-3)/1.5e-3)) # -thi2-sh = 30mV, Use -30mV instead of 15mV.
#####

class NaMitChannelMS(moose.HHChannel):
    """Na channel inherits from HHChannel."""
    def __init__(self, sh, VNa, *args):
        """Setup the Na channel with defaults"""
        moose.HHChannel.__init__(self,*args)
        self.Ek = VNa
        self.Gbar = GNa
        self.addField('ion')
        self.setField('ion','Na')
        self.Xpower = 3 # This will create HHGate instance xGate inside the Na channel
        self.Ypower = 1 # This will create HHGate instance yGate inside the Na channel
        ## Below gates get created after Xpower or Ypower are set to nonzero values
        ## I don't anymore have to explicitly create these attributes in the class
        #self.xGate = moose.HHGate(self.path + "/xGate")
        #self.yGate = moose.HHGate(self.path + "/yGate")
        self.xGate.A.xmin = VMIN
        self.xGate.A.xmax = VMAX
        self.xGate.A.xdivs = NDIVS
        self.xGate.B.xmin = VMIN
        self.xGate.B.xmax = VMAX
        self.xGate.B.xdivs = NDIVS
        self.yGate.A.xmin = VMIN
        self.yGate.A.xmax = VMAX
        self.yGate.A.xdivs = NDIVS
        self.yGate.B.xmin = VMIN
        self.yGate.B.xmax = VMAX
        self.yGate.B.xdivs = NDIVS
        
        v = VMIN
        
        for i in range(NDIVS+1):
            a = trap0(v-(tha+sh),Ra,qa)
            b = trap0(-v+(tha+sh),Rb,qa)
            mtau = 1/(a+b)/qt
            if mtau<mmin: mtau=mmin
            minf = a/(a+b)
            self.xGate.A[i] = minf/mtau
            self.xGate.B[i] = 1/mtau
            #self.xGate.tweakTau() # convert mtau and minf to A and B tables
            
            a = trap0(v-(thi1+sh),Rd,qd)
            b = trap0(-v+(thi2+sh),Rg,qg)
            htau = 1/(a+b)/qt
            if htau<hmin: htau=hmin
            hinf = 1/(1+math.exp((v-thinf-sh)/qinf))
            self.yGate.A[i] = hinf/htau
            self.yGate.B[i] = 1/htau
            #self.yGate.tweakTau() # convert htau and hinf tables to A and B tables.
            v = v + dv