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

 Download zip file 
Help downloading and running models
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;
/
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 = [5,77,105,47,98,16,8]
ccperc =  [ 0.1, 0.3, 0.5, 0.7, 0.9 ]
filename = 'out-0-0-g%dcc%gli0.499-v3.spk2'
from spikesreader import SpikesReader as SR
from geodist import glomdist as gd
fileout = '../out-frp-0.499.txt'

def glom2fr(sr, gids):
  nspk = 0.
  for _gid in gids:
    try:
      nspk += len([ t for t in sr.retrieve(_gid) if t > 0 ])
    except:
      pass
  return nspk/len(gids)

def glom2fr_mc(sr,glom):
  return glom2fr(sr,range(glom*5,(glom+1)*5))

def glom2fr_mt(sr,glom):
  return glom2fr(sr,range(glom*10+635,(glom+1)*10+635))


with open(fileout, 'w') as fo:
  for _ccperc in ccperc:
    try:
      _filename37 = filename%(37,_ccperc)
      sr37 = SR(_filename37)
      fr_mc_37 = glom2fr_mc(sr37, 37)
      fr_mt_37 = glom2fr_mt(sr37, 37)
      
      for _glom in gloms:
        try:
          _filename = filename%(_glom,_ccperc)
          sr = SR(_filename)
          fr_mc_37_2 = glom2fr_mc(sr, 37)
          fr_mt_37_2 = glom2fr_mt(sr, 37)
          
          d_mc = (fr_mc_37_2-fr_mc_37)/fr_mc_37
          d_mt = (fr_mt_37_2-fr_mt_37)/fr_mt_37
          x = ( round( gd(_glom, 37)/100)*100,  (_ccperc-0.5)/0.5, d_mc, d_mt )
          print fr_mc_37/2.,fr_mt_37/2.,gd(_glom, 37), _ccperc-0.5, d_mc, d_mt
          fo.write('%g %g %g %g\n'%x)
        except: pass
    except: pass
    

Loading data, please wait...