Parallel network simulations with NEURON (Migliore et al 2006)

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Accession:64229
The NEURON simulation environment has been extended to support parallel network simulations. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters.
Reference:
1 . Migliore M, Cannia C, Lytton WW, Markram H, Hines ML (2006) Parallel network simulations with NEURON. J Comput Neurosci 21:119-29 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu];
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netmod
parbulbNet
README *
cadecay.mod *
flushf.mod *
kA.mod *
kca.mod *
kfasttab.mod *
kM.mod *
kslowtab.mod *
lcafixed.mod *
nafast.mod *
nagran.mod *
nmdanet.mod *
bulb.hoc
calcisilag.hoc *
ddi_baseline.gnu *
ddi_baseline.ses *
experiment_ddi_baseline.hoc *
experiment_odour_baseline.hoc *
granule.tem *
init.hoc *
input.hoc *
input1 *
mathslib.hoc *
mitral.tem *
modstat
mosinit.hoc *
odour_baseline.gnu *
odour_baseline.ses *
par_batch1.hoc
par_bulb.hoc
par_calcisilag.hoc
par_experiment_ddi_baseline.hoc
par_granule.tem
par_init.hoc
par_input.hoc
par_mitral.tem
par_netpar.hoc
par_notes
parameters_ddi_baseline.hoc *
parameters_odour_baseline.hoc *
screenshot.png *
tabchannels.dat *
tabchannels.hoc *
test1.sh
                            
// experiment_ddi_baseline.hoc
// Olfactory bulb network model: experiment file
//   for dendrodendritic inhibition.
// Andrew Davison, The Babraham Institute, 2000.

// *** Set inputs and connections
set_no_input()
glomshock(20,2,5)
randomise_NMDA(NMDAweight,(0.5*NMDAweight)^2)

// *** Voltage clamp mitral cell
mit[3][3].GABAA.e = 0 // mV
objref vclamp
mit[3][3].soma vclamp = new SEClamp(0.5)
vclamp.rs = 2 // Mohm
vclamp.dur1 = 1
vclamp.amp1 = -65
vclamp.dur2 = 4000
vclamp.amp2 = -70
vclamp.dur3 = 0
vclamp.amp3 = -65

// *** Set-up recording
objref igabaa, tvec, vgran, vmit, iclamp
record_step = 0.1
record_vec_size = int(tstop/record_step)+1
igabaa = new Vector(record_vec_size)
tvec = new Vector(record_vec_size)
vgran = new Vector(record_vec_size)
vmit = new Vector(record_vec_size)
iclamp = new Vector(record_vec_size)
record_step = 0.1
igabaa.record(&mit[3][3].GABAA.i,record_step)
tvec.record(&t,record_step)
vgran.record(&gran[0][6].periph.v(0.5),record_step)
vmit.record(&mit[0][0].dend.v(0.5),record_step)
iclamp.record(&vclamp.i,record_step)

// *** Process data and print out results
proc print_results() {
  xopen("calcisilag.hoc")
  print_raster(fileroot)
  print_gran_raster(fileroot)
  print_gran_hist(1,fileroot)
  sprint(filename,"%s.curvs",fileroot)
  outfile.wopen(filename)
  for i = 0, tvec.size()-1 {
    outfile.printf("%8.3g %8.3g %8.3g %8.3g %8.3g \n",tvec.x[i],igabaa.x[i],vmit.x[i],vgran.x[i],iclamp.x[i])
  }
  outfile.close()
  print "Results printed to files"
}

xopen("ddi_baseline.ses")

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