Parallel network simulations with NEURON (Migliore et al 2006)

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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.
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):
Gap Junctions:
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at];
readme.html *
bgka.mod *
CaBK.mod *
ccanl.mod *
Gfluct2.mod *
gskch.mod *
hyperde3.mod *
ichan2.mod *
LcaMig.mod *
nca.mod *
tca.mod *
DG500_M7.hoc *
dgnetactivity.jpg *
dgnettraces.jpg *
initorig.hoc *
modstat *
mosinit.hoc *
RI10sp.hoc *
time *
Santhakumar V, Aradi I, Soltesz I (2005) Role of mossy fiber sprouting
and mossy cell loss in hyperexcitability: a network model of the dentate
gyrus incorporating cell types and axonal topography. /J Neurophysiol/ *93*:437-53

Note: a diagram of the model is one of the figures of the paper.
I cannot say at the moment how many states the model has because some
mod files cannot be used with
the variable time step method.

527 cells
 500 Granule, 9 compartments, 7 Mechanisms
 6 Basket, 17 compartments, 7 Mechanisms
 15 Mossy, 17 compartments, 8 Mechanisms
 6 HIPP, 13 compartments, 8 Mechanisms
11293 NetCon into 4875 Exp2Syn

300 ms,  2861 spikes generated, 50136 spikes delivered.

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