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

 Download zip file 
Help downloading and running models
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;
/
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 os
import sys
import math

sys.path.extend(["..","../channels/"])

from NaChannel import *
from KFastChannel import *
from KSlowChannel import *
from CaLChannel import *
from KAChannel import *
## use KCaChannel instead of KCaMPIChannel, in a non-MPI i.e. non-parallel run,
## to generate the KCaA.dat and KCaB.dat files.
#from KCaChannel import *
from KCaMPIChannel import *
## use KCaChannel_PG instead of KCaMPIChannel_PG, in a non-MPI i.e. non-parallel run,
## to generate the KCaA_PG.dat and KCaB_PG.dat files.
#from KCaChannel_PG import *
from KCaMPIChannel_PG import *
from CaPool import *
from KMChannel import *
from CaTChannel import *

from NaMitChannelMS import *
from KAChannelMS import *
from KDRChannelMS import *

import moose
from moose.neuroml import *

FARADAY = 96154.0 # Coulombs # from cadecay.mod : 1/(2*96154.0) = 5.2e-6 which is the Book of Genesis / readcell value
#FARADAY = 96485.3415 # Coulombs # from Wikipedia

def load_channels():
    # Na channels in /library should be called *Na* not *na*. No other channel should have Na in its name.
    # I search later for Na channels by string *Na*
    NaChannel("/library/Na_mit_usb")
    KFastChannel("/library/K2_mit_usb") ## CAUTION: K2 is Kfast
    KSlowChannel("/library/K_mit_usb") ## CAUTION: K is Kslow
    CaLChannel("/library/LCa3_mit_usb") # L-type Ca channel (high threshold)
    KAChannel("/library/KA_bsg_yka")
    KCaChannel("/library/Kca_mit_usb")
    KCaChannel_PG("/library/Kca_mit_usb_pg")
    CaPool("/library/Ca_mit_conc")
    KMChannel("/library/KM_bsg_upi")
    CaTChannel("/library/TCa_rat_ag") # T-type Ca channel (low threshold)
    # NaMitChannelMS(sh, Vna, MOOSEpathname)
    # mit Na and gran Na channels are different in sh and ENa. 
    NaMitChannelMS(10e-3, 50e-3, "/library/Na_mit_ms")
    NaMitChannelMS(0e-3, 50e-3, "/library/Na_mit_initialsegment_ms")
    # for Granule cell, maintaining the old name Na_rat_ms to avoid changing .p file (now invalid argument!),
    # even though this Na channel for granule cell is from Migliore and Shepherd 2008
    NaMitChannelMS(15e-3, 60e-3, "/library/Na_rat_ms")
    KAChannelMS("/library/KA_ms")
    KDRChannelMS("/library/KDR_ms")
    #self.context.readNeuroML(../channels/IhChannel.xml,"/library/Ih_cb")
    CML = ChannelML({'temperature':CELSIUS})
    CML.readChannelMLFromFile('../channels/Ih_cb.xml')
    CML.readChannelMLFromFile('../channels/TCa_d.xml')
    ## extras from neuroConstruct examples
    #CML.readChannelMLFromFile('../channels/CaHVA_Chan.xml')
    #CML.readChannelMLFromFile('../channels/CaL_Chan.xml')

def connect_CaConc(compartment_list):
    context = moose.PyMooseBase.getContext()
    #### Connect the Ca pools and channels
    #### Ca channels should have an extra field called 'ion' defined and set in MOOSE.
    #### Ca dependent channels like KCa should have an extra field called 'ionDependency' defined and set in MOOSE.
    #### Am connecting these at the very end so that all channels and pools have been created
    for compartment in compartment_list:
        if context.exists(compartment.path+'/Ca_mit_conc'): # Ca Pool
            caconc = moose.CaConc(compartment.path+'/Ca_mit_conc')
            for child in compartment.getChildren(compartment.id):
                neutralwrap = moose.Neutral(child)
                if neutralwrap.className == 'HHChannel':
                    channel = moose.HHChannel(child)
                    ### If 'ion' field is not present, the Shell returns '0', cribs and prints out a message but it does not throw an exception
                    if channel.getField('ion') == 'Ca':
                        channel.connect('IkSrc',caconc,'current')
                        #print 'Connected ',channel.path
                if neutralwrap.className == 'HHChannel2D':
                    channel = moose.HHChannel2D(child)
                    ### If 'ionDependency' field is not present, the Shell returns '0', cribs and prints out a message but it does not throw an exception
                    if channel.getField('ionDependency') == 'Ca':
                        caconc.connect('concSrc',channel,'concen')
                        #print 'Connected ',channel.path