JitCon: Just in time connectivity for large spiking networks (Lytton et al. 2008)

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Accession:106891
This simulation is primarily an illustration and is not well optimized for actually running large networks. jitcon.mod contains a large amount of C level code, understanding of which requires some knowledge of Neuron internals
Reference:
1 . Lytton WW, Omurtag A, Neymotin SA, Hines ML (2008) Just in time connectivity for large spiking networks Neural Comput 20(11):2745-56 [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): Epilepsy;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu];
Files displayed below are from the implementation
/
b07dec27_20091025
readme.html
jitcon.mod
misc.mod *
myexpsyn.mod
nstim.mod *
stats.mod
vecst.mod
batch_.hoc
bstick_net.hoc
mosinit.hoc
screenshot.jpg
xtmp
                            
: $Id: myexpsyn.mod,v 1.2 2007/12/28 02:51:31 billl Exp $

COMMENT
Functionally unchanged from original expsyn.mod which is POINT_PROCESS ExpSyn
Added are RANGE variables poid,poty,prid,prty which are
  postsynaptic_ID, presynaptic_ID, postsynaptic_cell_type, presynaptic_cell_type
  respectively
This was used to insure that JitCon hooks itself up to the correct synapse -- this turns out
  not to be necessary since the correct synapse will always be the one at the end of the list
ENDCOMMENT

NEURON {
	POINT_PROCESS expsyn
	RANGE tau, e, i, poid, poty, prid, prty
	NONSPECIFIC_CURRENT i
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(uS) = (microsiemens)
}

PARAMETER {
	tau = 0.1 (ms) <1e-9,1e9>
	e = 0	(mV)
}

ASSIGNED {
	v (mV)
	i (nA)
        poid poty prid prty
}

STATE {
	g (uS)
}

INITIAL {
	g=0
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	i = g*(v - e)
}

DERIVATIVE state {
	g' = -g/tau
}

NET_RECEIVE(weight (uS)) {
	state_discontinuity(g, g + weight)
}

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