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]
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
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 *

# ALL SI UNITS

class CaPool(moose.CaConc):
    def __init__(self, *args):
        moose.CaConc.__init__(self, *args)
        ## 0.05 is the value at which Ca settles in the PG cell,
        ## setting Ca_Base to 0.05 makes intial burstiness of PG cell 2012 go away,
        ## yet it makes no difference to its later firing!
        ## but setting it to 0.05 makes the mitral very low firing.
        ## From cadecay.mod but Book of Genesis says 5e-5 mol/m^3 is typical.
        self.CaBasal = 1e-5 # mol/m^3, same as mmol/litre = mMolar
        ## dunno why python wrapper has both CaBasal and Ca_Base
        ## setting Ca_Base to 0.05 makes no difference to PG cell 2012's
        ## firing or initial burstiness or Ca response.
        self.Ca_Base = 1e-5 # mol/m^3, same as mmol/litre = mMolar
        self.tau = 10e-3 # second # From cadecay.mod
        self.getContext().runG('setfield ' + self.path + ' ceiling 1e6')
        self.getContext().runG('setfield ' + self.path + ' floor 0.0')
        
    def connectCaChannels(self, channel_list):
        """Connects the Ca2+ channels in channel_list as a source of
        Ca2+ to the pool."""
        for channel in channel_list:
                if not hasattr(channel, 'connected_to_pool') or not channel.connected_to_pool:
                    channel.connect('IkSrc', self, 'current')
                    channel.connected_to_pool = True
                else:
                    print channel.path, 'already connected'
                
    def connectDepChannels(self, channel_list):
        """Connect channels in channel_list as dependent channels"""
        for channel in channel_list:
            if not hasattr(channel, 'connected_to_ca') or not channel.connected_to_ca:
                self.connect("concSrc", channel, "concen")
                #self.getContext().runG('addmsg '+self.path+' '+channel.path+' CONCEN1 Ca')
                channel.connected_to_ca = True
            else:
                print "WARNING: Ignoring non-KCaChannel", channel.path
# 
# capool.py ends here

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