Local variable time step method (Lytton, Hines 2005)

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Accession:33975
The local variable time-step method utilizes separate variable step integrators for individual neurons in the network. It is most suitable for medium size networks in which average synaptic input intervals to a single cell are much greater than a fixed step dt.
Reference:
1 . Lytton WW, Hines ML (2005) Independent variable time-step integration of individual neurons for network simulations. Neural Comput 17:903-21 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type:
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];
objref wbfile, wbsp, wbcell, wbinitv, tobj, wbsort
wbfile = new File()
wbfile.ropen("wb96fig3a-5atol.dat")
tobj = new Vector(wbfile.scanvar)
tobj.scanf(wbfile, tobj.size)
wbcell = new Vector()
wbcell.scanf(wbfile, tobj.size)
wbinitv = new Vector(100)
wbinitv.scanf(wbfile, 100)

wbsort = new Vector(100)
wbsort = wbinitv.sortindex
wbinitv.sort

objref wbsp[100]
proc sptimes() {
	for i=0, 99 {
		wbsp[i] = new Vector()
		wbsp[i].index(tobj, wbsp[i].indvwhere(wbcell, "==", wbsort.x[i]))
	}
}
sptimes()

proc vinit() {local i, dv
        for i = 0, ncell-1 {
                cells.object(i).soma.v(.5) = wbinitv.x[i]
        }
}

vinit()

delaymin = delaydel = 0
setdel()
varcur = 0
mcur = .001
setfreq()


proc cmprun() {local i
	run()
	for i=0, ncell-1 {
		wbsp[i].c.fill(i+1).mark(sp.g, wbsp[i], "|", 7, 2)
	}
	sp.g.flush()
}

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