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];
// NetGUI default section. Artificial cells, if any, are located here.
  create acell_home_
  access acell_home_

//Network cell templates
//Artificial cells
//   IF_IntervalFire


// modified from NetGUI hoc output to add the random interval

begintemplate IF_IntervalFire
public pp, connect2target, x, y, z, position, is_art, r, hseed, ranstart
external acell_home_
objref pp, r
proc init() {
  hseed = $1
  acell_home_ pp = new IntervalFire(.5)
  r = new Random()
  ranstart()
  pp.set_rand(r)
  r.uniform(10,20)
}
func ranstart() {
  return r.MCellRan4(hseed)
}
func is_art() { return 1 }
proc connect2target() { $o2 = new NetCon(pp, $o1) }
proc position(){x=$1  y=$2  z=$3}
endtemplate IF_IntervalFire

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