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 Comp Neurosci 21:110-119 [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
parscalebush
AMPA.mod *
arhRT03.mod *
cadecay.mod
cadRT03.mod
cah.mod
calRT03.mod
catRT03.mod *
GABAa.mod *
GABAb.mod *
intf.mod
k2RT03.mod *
kahpRT03.mod
kaRT03.mod *
kca.mod *
kcRT03.mod
kdr.mod
kdrp.mod
kdrRT03.mod *
kmRT03.mod *
misc.mod
myfit.mod
na.mod
nafRT03.mod *
nap.mod
napRT03.mod *
NMDA.mod *
nstim.mod
stats.mod
vecst.mod
batch.hoc
bg
bg_cvode.inc
boltz_cvode.inc
geneval_cvode.inc
geom.hoc
init.hoc
netcon.inc
network.hoc
nqsnet.hoc
nspike.dat
params.hoc
parnetwork.hoc
parnqsnet.hoc
perfrun.hoc
prebatch_.hoc
run.hoc
spkplt.hoc *
x_vs_nspike.hoc
                            
// $Id: params.hoc,v 1.3 2006/02/08 15:05:46 hines Exp $

//* general params
seed=3492
{vseed(seed)}

celsius = 37
dt = 1e-3
secondorder = 2
tstop = 500
runStopAt = tstop
steps_per_ms = 10
global_ra = 200
v_init = -60
erest = -60
irest = -60

//* conductances
gadjust3 = 1
gadjust = 0.4
sadjust = 2
gadjust2 = 0.45

proc fppm () { local i,j
    for i = 0, fpnum-1 if (pc.gid_exists(idfp + i)) {
        fp[i].soma { 
            insert fastpas   g_fastpas=0.000142*gadjust e_fastpas=erest+1
            insert na     gmax_na=0.04*sadjust 
            insert kdr    gmax_kdr=0.03*sadjust    mbaserate_kdr=0.05 
          }
        fp[i].dend[2] { 
            insert nap gmax_nap = 0.015 
            insert kdrp gmax_kdrp = 0.03 
          }
        for j=0,7 fp[i].dend[j] { 
            insert fastpas     g_fastpas = 0.000142*gadjust     e_fastpas = erest+1 
          }
      }
  }

proc tppm () { local i,j
    for i = 0, tpnum-1 if (pc.gid_exists(idtp + i)) { 
        tp[i].soma { 
            insert fastpas g_fastpas = 0.0001475*gadjust2  e_fastpas=erest-1 
            insert na gmax_na=0.03 
            insert kdr gmax_kdr=0.02 mbaserate_kdr=0.015 
            insert cah gmax_cah = 0.001 
            insert cadecay 
            insert kca gmax_kca = 0.001
          }
        for j=0,6 tp[i].dend[j] { 
            insert fastpas g_fastpas=0.0001475*gadjust2  e_fastpas=erest 
          }
      }
  }

proc b5pm () { local i,j
    for i=0,b5num-1 if (pc.gid_exists(idb5 + i)) { 
        bas5[i].soma { 
            insert fastpas g_fastpas = 0.0001475*gadjust3 e_fastpas = irest-1
            insert na gmax_na=0.08 
            insert kdr gmax_kdr=0.09
          }
        for j=0,5 bas5[i].dend[j] { 
            insert fastpas g_fastpas=0.0001475*gadjust3   e_fastpas=irest
          }
      }
    
    for i=84,b5num-1 if (pc.gid_exists(idb5 + i)) {
        bas5[i].soma { 
            insert cah gmax_cah=0.0005 
            insert cadecay taucaremov_cadecay = 100 
            insert kca gmax_kca=0.0025
          }
      }
  }

fppm()
tppm()
b5pm()

//* add extrinsic inputs
if (pc.gid_exists(idstim)) {
	nstim.pp.start=2
	nstim.pp.number=1
}

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