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
                            
RM = 12.0 # ohm m^2 from granule.tem
CM = 0.01 # F/m^2 from Bhalla and Bower 1993 ##### cannot find CM being set in granule.tem!!! though this is perhaps the NEURON default
RA = 0.5 # ohm m from Bhalla and Bower 1993 #### Cannot find RA being set in granule.tem!!!!! I don't think this is the NEURON default
#### actually RA is not used. psuedo compartments are used to model the inter-compartmental resistances.

EREST = -0.065 # Volts
sarea = 5e-9 # m^2 default surface area of soma

SURFACE_AREA_TOTAL	= 8353.0e-12	# m^2
LENGTH		= 50.0e-6		# m
SOMA_SAREA_FRAC	= 0.0136
PERIPH_SAREA_FRAC = 0.308
DEEP_SAREA_FRAC = 1 - SOMA_SAREA_FRAC - PERIPH_SAREA_FRAC
G_SOMA_PERI 	= 3.08e-6	# S.m^-2 from granule.tem
G_SOMA_DEEP 	= 4.34e-6    	# S.m^-2 from granule.tem

SOMASTIM = True
PERISTIM = False

IFULL = 0.0125e-9 # nA ### without electrode leak as here, need to halve the current to match Bhalla and Bower as the input resistance is higher.


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