Parallel odor processing by mitral and middle tufted cells in the OB (Cavarretta et al 2016, 2018)

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Accession:240116
"[...] experimental findings suggest that MC and mTC may encode parallel and complementary odor representations. We have analyzed the functional roles of these pathways by using a morphologically and physiologically realistic three-dimensional model to explore the MC and mTC microcircuits in the glomerular layer and deeper plexiform layers. [...]"
Reference:
1 . Cavarretta F, Burton SD, Igarashi KM, Shepherd GM, Hines ML, Migliore M (2018) Parallel odor processing by mitral and middle tufted cells in the olfactory bulb. Sci Rep 8:7625 [PubMed]
2 . Cavarretta F, Marasco A, Hines ML, Shepherd GM, Migliore M (2016) Glomerular and Mitral-Granule Cell Microcircuits Coordinate Temporal and Spatial Information Processing in the Olfactory Bulb. Front Comput Neurosci 10:67 [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 tufted middle cell; Olfactory bulb main interneuron granule MC cell; Olfactory bulb main interneuron granule TC cell; Olfactory bulb (accessory) mitral cell; Olfactory bulb main tufted cell external; Olfactory bulb short axon cell;
Channel(s): I A; I Na,t; I_Ks; I K;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; GabaA; NMDA;
Gene(s):
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; Action Potential Initiation; Active Dendrites; Long-term Synaptic Plasticity; Synaptic Integration; Synchronization; Pattern Recognition; Spatio-temporal Activity Patterns; Temporal Pattern Generation; Sensory coding; Sensory processing; Olfaction;
Implementer(s): Cavarretta, Francesco [francescocavarretta at hotmail.it]; Hines, Michael [Michael.Hines at Yale.edu];
Search NeuronDB for information about:  Olfactory bulb main interneuron granule MC cell; Olfactory bulb main tufted middle cell; Olfactory bulb main interneuron granule TC cell; GabaA; AMPA; NMDA; I Na,t; I A; I K; I_Ks; Gaba; Glutamate;
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modeldb-bulb3d
sim
ampanmda.mod
distrt.mod *
fi.mod
fi_stdp.mod *
gap.mod
Gfluct.mod
kamt.mod
kdrmt.mod
ks.mod
naxn.mod
orn.mod
ThreshDetect.mod *
all.py
all2all.py *
assembly.py
balance.py *
bindict.py
binsave.py
binspikes.py
blanes.hoc
blanes.py
blanes_exc_conn.txt
blanes6.dic
bulb3dtest.py
cancel.py
catfiles.sh
cellreader.py
cellwriter.py
cfg27.py
common.py
complexity.py *
convertdic.py
destroy_model.py
determine_connections.py
distribute.py *
dsac.py
Eta.txt *
fillgloms.py
fixnseg.hoc *
g_conn_stats.py
gapjunc.py
gen_weights.py
geodist.py
geodist.txt
getmitral.py
gidfunc.py
GJ.py
gj_nrn.hoc
Glom.py *
granule.hoc
granules.py
graphmeat.py
grow.py
growdef.py *
growout.py
job
Kod.txt *
lateral_connections.py
loadbalutil.py *
lpt.py *
mcgrow.py
MCrealSoma.py *
mgrs.py
misc.py
mitral.hoc
mkassembly.py
mkmitral.py
modeldata.py
mtgrow.py
MTrealSoma.py
MTrealSoma2.py
mtufted.hoc
multisplit_distrib.py
net_mitral_centric.py
Nod.txt *
odors.py
odorstim.py
odstim2.txt *
pad.txt *
params.py
parrun.py
pathdist.py
realgloms.txt *
runsim.py
spike2file.hoc *
spk2weight.py
split.py
subsetsim.py
test_complexity.py
txt2bin.py
util.py *
vrecord.py
weightsave.py
                            
from misc import *
import copy
__somar = [ [], [], [], [], [] ]
__somar[0] += [ [ -4.64988, -5.20346, 19.2301, 3.72505 ] ]
__somar[0] += [ [ -3.84717, -5.25629, 17.2755, 6.64771 ] ]
__somar[0] += [ [ -3.04446, -5.30912, 15.3209, 12.492 ] ]
__somar[0] += [ [ -2.24176, -5.36195, 13.3662, 17.2341 ] ]
__somar[0] += [ [ -1.43905, -5.41478, 11.4116, 20.3893 ] ]
__somar[0] += [ [ -0.636342, -5.4676, 9.45701, 23.5446 ] ]
__somar[0] += [ [ 0.166365, -5.52043, 7.50239, 25.5399 ] ]
__somar[0] += [ [ 0.969072, -5.57326, 5.54777, 27.321 ] ]
__somar[0] += [ [ 1.77178, -5.62609, 3.59315, 28.4545 ] ]
__somar[0] += [ [ 2.57449, -5.67892, 1.63853, 28.5444 ] ]
__somar[0] += [ [ 3.37719, -5.73175, -0.316091, 28.6342 ] ]
__somar[0] += [ [ 4.1799, -5.78458, -2.27071, 28.7241 ] ]
__somar[0] += [ [ 4.98261, -5.8374, -4.22533, 28.8139 ] ]
__somar[0] += [ [ 5.78532, -5.89023, -6.17995, 28.7778 ] ]
__somar[0] += [ [ 6.58802, -5.94306, -8.13457, 27.5509 ] ]
__somar[0] += [ [ 7.39073, -5.99589, -10.0892, 24.662 ] ]
__somar[0] += [ [ 8.19344, -6.04872, -12.0438, 21.7659 ] ]
__somar[0] += [ [ 8.99615, -6.10155, -13.9984, 18.8697 ] ]
__somar[0] += [ [ 9.79885, -6.15438, -15.9531, 15.9736 ] ]
__somar[0] += [ [ 10.6016, -6.2072, -17.9077, 12.8157 ] ]
__somar[0] += [ [ 11.4043, -6.26003, -19.8623, 7.15979 ] ]
__somar[1] += [ [ -6.09478, -0.258876, 17.4299, 3.49374 ] ]
__somar[1] += [ [ -5.25081, -0.282379, 16.3378, 5.90019 ] ]
__somar[1] += [ [ -4.40684, -0.305882, 15.2456, 9.07648 ] ]
__somar[1] += [ [ -3.56287, -0.329384, 14.1535, 11.2008 ] ]
__somar[1] += [ [ -2.7189, -0.352887, 13.0614, 13.4637 ] ]
__somar[1] += [ [ -1.87493, -0.37639, 11.9692, 14.2691 ] ]
__somar[1] += [ [ -1.03096, -0.399893, 10.8771, 15.0652 ] ]
__somar[1] += [ [ -0.18699, -0.423396, 9.78496, 15.3968 ] ]
__somar[1] += [ [ 0.656979, -0.446899, 8.69283, 15.3743 ] ]
__somar[1] += [ [ 1.50095, -0.470402, 7.60069, 15.3519 ] ]
__somar[1] += [ [ 2.34492, -0.493905, 6.50856, 15.3292 ] ]
__somar[1] += [ [ 3.18889, -0.517408, 5.41643, 15.2902 ] ]
__somar[1] += [ [ 4.03286, -0.540911, 4.32429, 15.2423 ] ]
__somar[1] += [ [ 4.87683, -0.564414, 3.23216, 15.0648 ] ]
__somar[1] += [ [ 5.72079, -0.587917, 2.14003, 14.7259 ] ]
__somar[1] += [ [ 6.56476, -0.61142, 1.04789, 14.3006 ] ]
__somar[1] += [ [ 7.40873, -0.634923, -0.0442405, 13.2035 ] ]
__somar[1] += [ [ 8.2527, -0.658426, -1.13637, 11.9114 ] ]
__somar[1] += [ [ 9.09667, -0.681929, -2.22851, 9.90796 ] ]
__somar[1] += [ [ 9.94064, -0.705432, -3.32064, 6.99624 ] ]
__somar[1] += [ [ 10.7846, -0.728935, -4.41277, 4.04732 ] ]
__somar[2] += [ [ -6.09478, -0.258876, 17.4299, 3.49374 ] ]
__somar[2] += [ [ -5.25081, -0.282379, 16.3378, 5.90019 ] ]
__somar[2] += [ [ -4.40684, -0.305882, 15.2456, 9.07648 ] ]
__somar[2] += [ [ -3.56287, -0.329384, 14.1535, 11.2008 ] ]
__somar[2] += [ [ -2.7189, -0.352887, 13.0614, 13.4637 ] ]
__somar[2] += [ [ -1.87493, -0.37639, 11.9692, 14.2691 ] ]
__somar[2] += [ [ -1.03096, -0.399893, 10.8771, 15.0652 ] ]
__somar[2] += [ [ -0.18699, -0.423396, 9.78496, 15.3968 ] ]
__somar[2] += [ [ 0.656979, -0.446899, 8.69283, 15.3743 ] ]
__somar[2] += [ [ 1.50095, -0.470402, 7.60069, 15.3519 ] ]
__somar[2] += [ [ 2.34492, -0.493905, 6.50856, 15.3292 ] ]
__somar[2] += [ [ 3.18889, -0.517408, 5.41643, 15.2902 ] ]
__somar[2] += [ [ 4.03286, -0.540911, 4.32429, 15.2423 ] ]
__somar[2] += [ [ 4.87683, -0.564414, 3.23216, 15.0648 ] ]
__somar[2] += [ [ 5.72079, -0.587917, 2.14003, 14.7259 ] ]
__somar[2] += [ [ 6.56476, -0.61142, 1.04789, 14.3006 ] ]
__somar[2] += [ [ 7.40873, -0.634923, -0.0442405, 13.2035 ] ]
__somar[2] += [ [ 8.2527, -0.658426, -1.13637, 11.9114 ] ]
__somar[2] += [ [ 9.09667, -0.681929, -2.22851, 9.90796 ] ]
__somar[2] += [ [ 9.94064, -0.705432, -3.32064, 6.99624 ] ]
__somar[2] += [ [ 10.7846, -0.728935, -4.41277, 4.04732 ] ]
__somar[3] += [ [ -2.23481, -53.7362, 14.2419, 2.99861 ] ]
__somar[3] += [ [ -1.76314, -53.8338, 12.9902, 5.47905 ] ]
__somar[3] += [ [ -1.29148, -53.9313, 11.7385, 7.98081 ] ]
__somar[3] += [ [ -0.819817, -54.0289, 10.4868, 10.0703 ] ]
__somar[3] += [ [ -0.348154, -54.1264, 9.2351, 11.4542 ] ]
__somar[3] += [ [ 0.12351, -54.2239, 7.9834, 12.3129 ] ]
__somar[3] += [ [ 0.595173, -54.3215, 6.7317, 13.3961 ] ]
__somar[3] += [ [ 1.06684, -54.419, 5.48, 16.5383 ] ]
__somar[3] += [ [ 1.5385, -54.5166, 4.22831, 19.1186 ] ]
__somar[3] += [ [ 2.01016, -54.6141, 2.97661, 19.7045 ] ]
__somar[3] += [ [ 2.48183, -54.7117, 1.72491, 20.2903 ] ]
__somar[3] += [ [ 2.95349, -54.8092, 0.473214, 20.0805 ] ]
__somar[3] += [ [ 3.42515, -54.9068, -0.778484, 19.6602 ] ]
__somar[3] += [ [ 3.89682, -55.0043, -2.03018, 19.1795 ] ]
__somar[3] += [ [ 4.36848, -55.1019, -3.28188, 18.1662 ] ]
__somar[3] += [ [ 4.84014, -55.1994, -4.53358, 16.7538 ] ]
__somar[3] += [ [ 5.31181, -55.2969, -5.78527, 14.8449 ] ]
__somar[3] += [ [ 5.78347, -55.3945, -7.03697, 12.936 ] ]
__somar[3] += [ [ 6.25513, -55.492, -8.28867, 10.3131 ] ]
__somar[3] += [ [ 6.7268, -55.5896, -9.54037, 6.51347 ] ]
__somar[3] += [ [ 7.19846, -55.6871, -10.7921, 3.56534 ] ]
__somar[4] += [ [ -11.6624, -5.98159, 39.7401, 2.53773 ] ]
__somar[4] += [ [ -10.108, -5.84634, 38.8583, 3.66685 ] ]
__somar[4] += [ [ -8.55354, -5.7111, 37.9764, 5.31313 ] ]
__somar[4] += [ [ -6.99909, -5.57586, 37.0945, 6.31607 ] ]
__somar[4] += [ [ -5.44464, -5.44061, 36.2126, 7.29106 ] ]
__somar[4] += [ [ -3.89019, -5.30537, 35.3307, 8.08265 ] ]
__somar[4] += [ [ -2.33574, -5.17013, 34.4488, 8.85495 ] ]
__somar[4] += [ [ -0.781296, -5.03489, 33.567, 9.49124 ] ]
__somar[4] += [ [ 0.773151, -4.89964, 32.6851, 9.94162 ] ]
__somar[4] += [ [ 2.3276, -4.7644, 31.8032, 10.3171 ] ]
__somar[4] += [ [ 3.88205, -4.62916, 30.9213, 10.4725 ] ]
__somar[4] += [ [ 5.43649, -4.49392, 30.0394, 10.5889 ] ]
__somar[4] += [ [ 6.99094, -4.35867, 29.1576, 10.7002 ] ]
__somar[4] += [ [ 8.54539, -4.22343, 28.2757, 10.8104 ] ]
__somar[4] += [ [ 10.0998, -4.08819, 27.3938, 10.7998 ] ]
__somar[4] += [ [ 11.6543, -3.95294, 26.5119, 10.6434 ] ]
__somar[4] += [ [ 13.2087, -3.8177, 25.63, 10.2144 ] ]
__somar[4] += [ [ 14.7632, -3.68246, 24.7481, 9.67498 ] ]
__somar[4] += [ [ 16.3176, -3.54722, 23.8663, 8.2052 ] ]
__somar[4] += [ [ 17.8721, -3.41197, 22.9844, 5.77718 ] ]
__somar[4] += [ [ 19.4265, -3.27673, 22.1025, 3.22379 ] ]

N_SOMA = len(__somar)

def realSoma(i, p):
    soma1 = copy.deepcopy(__somar[i])

    # translation vector calculation
    vec = centroid(soma1)
    for j in range(3): vec[j] = p[j] - vec[j]
    
    # translate
    for x in soma1:
        for j in range(3):
            x[j] += vec[j]

    return soma1