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;
# -*- coding: utf-8 -*-

import math, os
import pickle

from pylab import *

## USAGE: python2.6 plot_corrs.py

sys.path.extend(["..","../networks","../generators","../simulations"])

from networkConstants import * # has central_glom
from data_utils import *
from calc_corrs import *

from results_catalogue import *

fig1 = figure(facecolor='none') # 'none' is transparent
## A super axes to set common x and y axes labels
bigAxes1 = fig1.add_axes([0.1,0.1,0.8,0.8],frameon=False) # hide frame
#bigAxes1.set_xticks([0,1,2,3])
#bigAxes1.set_xticklabels(['none', 'singles',\
#    's+joints', 's+j+PGs'],fontsize=20)
bigAxes1.set_xticks([])
bigAxes1.set_yticks([])
bigAxes1.text(-0.1,0.3,'spiking probability', fontsize=24, rotation='vertical')
bigAxes1.text(-0.1,-0.11,'inhibition: none, singles, s+joints, s+j+PGs',\
    fontsize=24, rotation='horizontal')
bigAxes1.set_title('Cross-Correlogram peak',fontsize=36)

fig2 = figure(facecolor='none') # 'none' is transparent
## A super axes to set common x and y axes labels
bigAxes2 = fig2.add_axes([0.1,0.1,0.8,0.8],frameon=False) # hide frame
#bigAxes2.set_xticks([0,1,2,3])
#bigAxes2.set_xticklabels(['none', 'singles',\
#    's+joints', 's+j+PGs'],fontsize=20)
bigAxes2.set_xticks([])
bigAxes2.set_yticks([])
bigAxes2.text(-0.1,-0.11,'inhibition: none, singles, s+joints, s+j+PGs',\
    fontsize=24, rotation='horizontal')
bigAxes2.set_title('Binned Cross-Correlation peak',fontsize=36)

fig3 = figure(facecolor='none') # 'none' is transparent
## A super axes to set common x and y axes labels
bigAxes3 = fig3.add_axes([0.1,0.1,0.8,0.8],frameon=False) # hide frame
#bigAxes3.set_xticks([0,1,2,3])
#bigAxes3.set_xticklabels(['none', 'singles',\
#    's+joints', 's+j+PGs'],fontsize=20)
bigAxes3.set_xticks([])
bigAxes3.set_yticks([])
bigAxes3.text(-0.1,0.3,'time(s)', fontsize=24, rotation='vertical')
bigAxes3.text(-0.1,-0.11,'inhibition: none, singles, s+joints, s+j+PGs',\
    fontsize=24, rotation='horizontal')
bigAxes3.set_title('Cross-Correlogram shift',fontsize=36)

plotnum = 1
for runnum in range(len(filelist[0])):
    corrgramlist = []
    corrgrammaxlist = []
    corrgrampeaklist = []
    corrlist = []
    print seeds[runnum]
    for filename in array(filelist)[:,runnum]:
        filenamefull = '../results/odor_morphs/'+filename
        (air_corr,odorA_corr,odorB_corr),\
            (tcorrlist,airxcorrgram,odorAxcorrgram,odorBxcorrgram)\
            = calc_corrs(filenamefull, norm_str='overall')
        corrgramlist.append([airxcorrgram,odorAxcorrgram,odorBxcorrgram])
        maxes = [max(airxcorrgram),max(odorAxcorrgram),max(odorBxcorrgram)]
        peaks = [ where(airxcorrgram==maxes[0])[0],\
            where(odorAxcorrgram==maxes[1])[0],
            where(odorBxcorrgram==maxes[2])[0] ]
        if len(peaks[0])>1 or len(peaks[1])>1 or len(peaks[2])>1:
            print "Multiple peaks for",filenamefull,peaks
        corrgrammaxlist.append(maxes)
        ## binwidth = 1e-3 for xcorrgram, convert bin index to time shift
        peaks = ( array([mean(peaks[0]),mean(peaks[1]),mean(peaks[2])]) - 1 ) * 1e-3 - 0.5
        corrgrampeaklist.append(peaks)
        corrlist.append([air_corr,odorA_corr,odorB_corr])
    corrlist = array(corrlist)
    corrgramlist = array(corrgramlist)
    corrgrammaxlist = array(corrgrammaxlist)
    corrgrampeaklist = array(corrgrampeaklist)
    
    ## hardcoded - I know there are 4 files
    ax1 = fig1.add_subplot(2,3,plotnum)
    ax1.set_xticks([])
    ax1.plot(corrgrammaxlist[:,0],color=(0,0,0),linewidth=2)
    ax1.plot(corrgrammaxlist[:,1],color=(1,0,0),linewidth=2)
    ax1.plot(corrgrammaxlist[:,2],color=(0,1,0),linewidth=2)
    #ymax = ax1.get_ylim()[1]+0.01
    ## very important to give it after the plot functions else autoscales
    #ax1.set_ylim(-0.01,ymax)
    #ax1.set_yticks([0,ymax])
    #ax1.set_yticklabels(['0','%0.2f'%ymax],size='large')
    ## or set autoscaling off - gca().set_autoscale_on(False)
    ## - taken from http://old.nabble.com/ylim-does-not-work-td19000814.html
    ax1.set_title( str(seeds[runnum]), size='large')

    ## hardcoded - I know there are 4 files
    ax3 = fig3.add_subplot(2,3,plotnum)
    ax3.set_xticks([])
    #ax3.plot(corrgrampeaklist[:,0],color=(0,0,0),linewidth=2)
    #ax3.plot(corrgrampeaklist[:,1],color=(1,0,0),linewidth=2)
    #ax3.plot(corrgrampeaklist[:,2],color=(0,1,0),linewidth=2)
    ax3.plot(corrgramlist[3,0],color=(0,0,0),linewidth=2)
    ax3.plot(corrgramlist[3,2],color=(0,1,0),linewidth=2)
    ax3.plot(corrgramlist[3,1],color=(1,0,0),linewidth=2)
    ax3.set_title( str(seeds[runnum]), size='large')

    ## hardcoded - I know there are 4 files
    ax2 = fig2.add_subplot(2,3,plotnum)
    ax2.set_xticks([])
    ax2.plot(corrlist[:,0],color=(0,0,0),linewidth=2)
    ax2.plot(corrlist[:,1],color=(1,0,0),linewidth=2)
    ax2.plot(corrlist[:,2],color=(0,1,0),linewidth=2)
    #ymax = ax1.get_ylim()[1]+0.01
    ## very important to give it after the plot functions else autoscales
    #ax2.set_ylim(-0.01,ymax)
    #ax2.set_yticks([0,ymax])
    #ax2.set_yticklabels(['0','%0.2f'%ymax],size='large')
    ## or set autoscaling off - gca().set_autoscale_on(False)
    ## - taken from http://old.nabble.com/ylim-does-not-work-td19000814.html
    ax2.set_title( str(seeds[runnum]), size='large')

    plotnum += 1

show()

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