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
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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: nstim.mod,v 1.1 2006/02/08 11:09:26 hines Exp $

NEURON	{ 
  ARTIFICIAL_CELL NStim
  RANGE interval, number, start, end
  RANGE noise,type,id
}

PARAMETER {
  interval	= 10 (ms) <1e-9,1e9>: time between spikes (msec)
  number	= 10 <0,1e9>	: number of spikes
  start		= 50 (ms)	: start of first spike
  noise		= 0 <0,1>	: amount of randomeaness (0.0 - 1.0)
  end		= 1e9 (ms)	: time to terminate train
}

ASSIGNED {
  event (ms)
  on
  endt (ms)
  type
  id
}

CONSTRUCTOR {
  VERBATIM 
  { if (ifarg(2)) { id= *getarg(2); } else { id= -1; }
    if (ifarg(3)) { type= *getarg(3); } else { type= 1; }
  }
  ENDVERBATIM
}

PROCEDURE seed (x) {
  set_seed(x)
}

INITIAL {
  on = 0
  if (noise < 0) { noise = 0 }
  if (noise > 1) { noise = 1 }
  if (interval <= 0.) { interval = .01 (ms) }
  if (start>=0 && number>0 && end>0) {
    event = start + invl(interval) - interval*(1. - noise)
    if (event < 0) { event = 0 }
    net_send(event, 3)
  }
}	

PROCEDURE init_sequence (t(ms)) {
  if (number > 0) {
    on = 1
    event = t
    endt = t + 1e-6 + interval*(number-1)
  }
}

FUNCTION invl (mean (ms)) (ms) {
  if (noise == 0) {
    invl = mean
  } else {
    invl = (1. - noise)*mean + noise*mean*exprand(1)
  }
}

NET_RECEIVE (w) {
  if (flag == 0) { : external event
    if (w > 0 && on == 0) { : turn on spike sequence
      init_sequence(t)
      net_send(0, 1)
    } else if (w < 0 && on == 1) { : turn off spiking
      on = 0
    }
  }
  if (flag == 3) { : from INITIAL
    if (on == 0) {
      init_sequence(t)
      net_send(0, 1)
    }
  }
  if (flag == 1 && on == 1) {
    net_event(t)
    event = event + invl(interval)
    if (event > endt || event > end) {
      on = 0
    } else {
      net_send(event - t, 1)
    }
  }
}

FUNCTION fflag () { fflag=1 }

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