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
                            
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    <meta:notes>ChannelML file based on Traub et al. 2003</meta:notes>

    <channel_type name="cal" density="yes">
        
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            <meta:issue>In original mod, m is initialised to 0, as opposed to minf at t=0. ChannelML impl corrects this</meta:issue>
            <meta:issue>In original mod ca is the ion transmitted through the channel (so internal conc is changed), but reversal potential of calcium (eca) isn't used in current calculation</meta:issue>
            <meta:contributor>
                <meta:name>Yoana Dimitrova</meta:name>
            </meta:contributor>
            <meta:contributor>
                <meta:name>Padraig Gleeson</meta:name>
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        <meta:notes>High threshold, long lasting Calcium L-type current. Based on NEURON port of FRB L2/3 model from Traub et al 2003. Same channel used in Traub et al 2005</meta:notes>
        
        <meta:authorList>
            <meta:modelAuthor>
                <meta:name>Maciej Lazarewicz</meta:name>
                <meta:comment>Conversion of FORTRAN model to NEURON. See Traub et al 2003 for detailed origin of channels</meta:comment>
            </meta:modelAuthor>
            <meta:modelAuthor>
                <meta:name>Roger D Traub</meta:name>
                <meta:comment>Conversion of FORTRAN model to NEURON. See Traub et al 2003 for detailed origin of channels</meta:comment>
            </meta:modelAuthor>
            
            
            <meta:modelTranslator>
                <meta:name>Padraig Gleeson</meta:name>
                <meta:institution>UCL</meta:institution>
                <meta:email>p.gleeson - at - ucl.ac.uk</meta:email>
            </meta:modelTranslator>
            <meta:modelTranslator>
                <meta:name>Yoana Dimitrova</meta:name>
                <meta:institution>UCL</meta:institution>
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        </meta:authorList>

        <meta:publication>
            <meta:fullTitle>Roger D. Traub, Eberhard H. Buhl, Tengis Gloveli, and Miles A. Whittington                
Fast Rhythmic Bursting Can Be Induced in Layer 2/3 Cortical Neurons by Enhancing Persistent Na+ Conductance or by Blocking BK Channels
J Neurophysiol 89: 909-921, 2003</meta:fullTitle>
            <meta:pubmedRef>http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=12574468</meta:pubmedRef>
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        <meta:publication>
            <meta:fullTitle>Roger D. Traub, Diego Contreras, Mark O. Cunningham, Hilary Murray, Fiona E. N. LeBeau, Anita Roopun, Andrea Bibbig, W. Bryan Wilent, Michael J. Higley, and Miles A. Whittington
Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts.
J. Neurophysiol. 93, 2194-2232, 2005</meta:fullTitle>
            <meta:pubmedRef>http://www.ncbi.nlm.nih.gov/pubmed/15525801?dopt=Abstract</meta:pubmedRef>
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        <current_voltage_relation cond_law="ohmic" ion="ca" default_gmax="0.5" default_erev="125" charge="2" fixed_erev="yes">
            
            <gate name="m" instances="2">
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                <open_state id="m" fraction="1"/>
                
                     <!-- An *incorrect* initialisation value for this, in order to compare to original mod file. Normally ignored-->
                <initialisation value="0"/> 
                     
                <transition name="alpha" from="m0" to="m" expr_form="sigmoid" rate="1.6" scale="-13.888889" midpoint="5" />
                     
                <transition name="beta" from="m" to="m0" expr_form="exp_linear" rate="0.1" scale="-5" midpoint="-8.9" />
                    
            </gate>
            
        </current_voltage_relation> 
        

        <impl_prefs>
            <comment>Using broad range of voltages for sufficient coverage</comment>
            <table_settings max_v="60" min_v="-120" table_divisions="741"/>
        </impl_prefs>
        
    </channel_type>
</channelml>

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