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. [...]"
References:
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]
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 GLU cell; Olfactory bulb main interneuron granule MC GABA cell; Olfactory bulb main interneuron granule TC GABA 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 GABA cell; Olfactory bulb main tufted middle GLU cell; Olfactory bulb main interneuron granule TC GABA cell; GabaA; AMPA; NMDA; I Na,t; I A; I K; I_Ks; Gaba; Glutamate;
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modeldb-bulb3d
vis
bulbdef.py
bulbdict.py
bulbgui.py
bulbvis.py
cellreader.py
cellwriter.py
cfg27.py
dummysyns.txt
Eta.txt *
firing.py
geodist.py
geodist.txt
ggid2type.txt
gidfunc.py
glomdist.py
granules.py
granules.txt
graphmeat.py
growdef.py *
ipsc.py
ispkdata.py
Kod.txt *
misc.py
Nod.txt *
odors.py
odstim2.txt *
pad.txt *
realgloms.txt *
spikes.py
spikesreader.py
spk2gd.py
spk2weight.py
spkgraph.py
winflag.txt
                            
gloms = [77,105,47,98,16,8,5] #+[2,10,11,17,34,32]
#filename = 'out-0-0-g%d-ipsc-d17Ri150i0.008i0.018sigexp4sl5p0-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.2-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15v2-nogj-%d-0.5.txt'

#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005-%d-0.5.txt'
#filename = '../out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005na0.02625-%d-0.5.txt'
#filename = '../out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005na0.027-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e1.25f0.064-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15f0.064-%d-0.5.txt'
filename = 'out-0-0-g%d-ipsc-e1.25t0.512-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.017-nogj-kdr0.005na0.0275-%d-0.5.txt'
#filename = '../out-0-0-g%d-ipsc-e0.15i0.017-nogj-kdr0.005na0.027-%d-0.5.txt'
#filename = '../out-0-0-g%d-ipsc-e0.15i0.017-nogj-kdr0.005na0.027-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005na0.0275-%d-0.5.txt' #<< okay
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005na0.03-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005s0.004-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005na0.035-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.0050625-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.0050625ka0.007-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.0050625ka0.009-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005125-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.00525-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.005375-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.0055-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.006-%d-0.5.txt'
#filename = 'out-0-0-g%d-ipsc-e0.15i0.018-nogj-kdr0.007-%d-0.5.txt'
from spikesreader import SpikesReader as SR
from geodist import glomdist as gd


def readvm(filename):
  v = []
  fi = open(filename, 'r')
  l = fi.readline()
  while l:
    v.append(float(l.split()[1]))
    l = fi.readline()
  fi.close()
  return min(v)

def glom2v(filename, glom, gids):
  m = 0.
  for _gid in gids:
    m += readvm(filename%(glom,_gid))
  return m/len(gids)+55

def glom2v_mc(filename,glom):
  return glom2v(filename, glom,range(37*5,(37+1)*5))

def glom2v_mt(filename,glom):
  return glom2v(filename,glom,range(37*10+635,(37+1)*10+635))

data = []
v_mt_37 = glom2v_mt(filename, 37)
v_mc_37 = glom2v_mc(filename, 37)
for glom in gloms:
  try:
    v_mt = glom2v_mt(filename, glom)
    v_mc = glom2v_mc(filename, glom)
    data.append((gd(glom,37),v_mt/v_mt_37,v_mc/v_mc_37))
  except:
    print glom, 'is absent'
data = sorted(data)
fo = open('../outt.xt', 'w')
print filename
for x in data:
  print '%g %g %g'%x
  fo.write('%g %g %g\n'%x)
fo.close()
print '\n'

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