Synchrony by synapse location (McTavish et al. 2012)

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Accession:144054
This model considers synchrony between mitral cells induced via shared granule cell interneurons while taking into account the spatial constraints of the system. In particular, since inhibitory inputs decay passively along the lateral dendrites, this model demonstrates that an optimal arrangement of the inhibitory synapses will be near the cell bodies of the relevant mitral cells.
Reference:
1 . McTavish TS, Migliore M, Shepherd GM, Hines ML (2012) Mitral cell spike synchrony modulated by dendrodendritic synapse location. Front Comput Neurosci 6:3 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron granule MC GABA cell;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s): GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Synchronization; Olfaction;
Implementer(s): McTavish, Thomas S [thomas.mctavish at yale.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron granule MC GABA cell; GabaB; AMPA; NMDA; I Na,t; I A; I K;
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mctavish_syncbylocation
src
ampanmda.mod
fi.mod
kamt.mod
kdrmt.mod
naxn.mod
ThreshDetect.mod *
allsynhinton.hoc *
analysis.py
animtest.py
antest.ses *
bulbspikes.py
clear.hoc
connect.hoc
control.ses
default.hoc
granule.hoc *
hinton.hoc
init.hoc *
iterator.hoc *
lptiter.hoc
mgrs.hoc
michele_movie.hoc
mitral.hoc
mosinit.hoc
net.hoc
param.hoc
params.py
parinit.hoc
pattern.hoc
perfrun.hoc
show.hoc
showw.hoc
somesyn.hoc *
sortspike *
split.hoc
start.hoc
start.ses
stimodors.hoc
subset.hoc
subset_control.ses *
synweightsnapshot.py
viewspikes.hoc
viewspikes1.hoc
weight_movie.hoc
weightsave.hoc
                            
// write weight file, read weight file, initialize weights
// weight file format is
//nweight
//t
//srcgid targid s w   : nweight of these
//any number of above two

////////create a weight file
weight_start_ = 1e9
weight_interval_ = 1e9
objref fih_weight_, weight_file_
proc weight_snapshots() {local i, nw   localobj f
	weight_file_ = new File($s1)
	f = weight_file_
	weight_start_ = $2
	weight_interval_ = $3
	fih_weight_ = new FInitializeHandler(2, "w1_()")
	nw = 0
	for i=0, mgrs_list.count-1 {
		if (object_id(mgrs_list.object(i).md2ampanmda)) { nw += 1 }
		if (object_id(mgrs_list.object(i).gd2fi)) { nw += 1 }
	}
	nw = pc.allreduce(nw,1)
	if (pc.id == 0) {
		f.wopen()
		f.printf("%d\n", nw)
		f.close()
	}
}

proc w1_() { cvode.event(weight_start_, "w2_()") }

proc w2_() {local i  localobj f
	f = weight_file_
	for pnm.serialize() {
		f.aopen()
		if (pc.id == 0) {
			f.printf("%g\n", t)
		}
		for i=0, mgrs_list.count-1 {
			if (write_weights_normalized) {
				f.printf("%s\n", mgrs_list.object(i).ws_str_normalized().s)
			} else {
				f.printf("%s\n", mgrs_list.object(i).ws_str().s)
			}
		}
		f.close()
	}
	cvode.event(t + weight_interval_, "w2_()")
}
//////////// end of create a weight file

/////////// initialize weight from first group of a weight file
objref fih_weight_init_, weight_init_file_
proc weight_initialize() {
	weight_init_file_ = new File($s1)
	// after NET_RECEIVE INITIAL
	fih_weight_init_ = new FInitializeHandler(1, "w3_()")
}

proc w3_() {local i, nw, srcgid, targid, s, w, sgid \
    localobj f, map, newmap, mgrs, p, nc, syn, ncl
	f = weight_init_file_
	f.ropen()
	nw = f.scanvar()
	f.scanvar() // discard t
	p = new PythonObject()
	nrnpython("newmap = lambda key, value : {key:value}")
	map = p.newmap(-1,0)
	for i=0, nw - 1 {
		srcgid = f.scanvar
		targid = f.scanvar
		s = f.scanvar // Sigmoid location
		w = f.scanvar // weight
		sgid = syn_gid(srcgid, targid)
//		if (pc.gid_exists(sgid)) {// correct even if multisplit
			// no way at present to efficiently derive the
			// MGRS from the srcgid, targid but we know it
			// exists. So save data in a Python map and
			// retrieve next loop
			map.update(p.newmap(sgid, s))
//printf("map %d %d %d %d\n", srcgid, targid, ncell, s)
//		}
	}
	f.close()
	// sweep mgrs_list
	for i=0, mgrs_list.count-1 {
		mgrs = mgrs_list.object(i)
		if (object_id(mgrs.gd2fi)) {
			s = map.__getitem__(mgrs.md_gid)
//printf("%d %d %g\n", mgrs.granule_gid, mgrs.mitral_gid, s)
			mgrs.set_sm(s)
		}
		if (object_id(mgrs.md2ampanmda)) {
			s = map.__getitem__(mgrs.gd_gid)
//printf("%d %d %g\n", mgrs.mitral_gid, mgrs.granule_gid, s)
			mgrs.set_sg(s)
		}
	}
}

proc weight_initialize_normalized() {
weight_init_file_ = new File($s1)
    // after NET_RECEIVE INITIAL
    fih_weight_init_ = new FInitializeHandler(1, "w3_normalized()")
}

proc w3_normalized() {local i, nw, srcgid, targid, s, w, sgid \
    localobj f, map, newmap, mgrs, p, nc, syn, ncl
    f = weight_init_file_
    f.ropen()
    nw = f.scanvar()
    f.scanvar() // discard t
    p = new PythonObject()
    nrnpython("newmap = lambda key, value : {key:value}")
    map = p.newmap(-1,0)
    for i=0, nw - 1 {
        srcgid = f.scanvar
        targid = f.scanvar
        s = f.scanvar
        w = f.scanvar
        sgid = syn_gid(srcgid, targid)
        //		if (pc.gid_exists(sgid)) {// correct even if multisplit
        // no way at present to efficiently derive the
        // MGRS from the srcgid, targid but we know it
        // exists. So save data in a Python map and
        // retrieve next loop
        map.update(p.newmap(sgid, w))
        //printf("map %d %d %d %d\n", srcgid, targid, ncell, s)
        //		}
    }
    f.close()
    // sweep mgrs_list
    for i=0, mgrs_list.count-1 {
        mgrs = mgrs_list.object(i)
        if (object_id(mgrs.gd2fi)) {
            w = map.__getitem__(mgrs.md_gid)
            //printf("%d %d %g\n", mgrs.granule_gid, mgrs.mitral_gid, w)
            mgrs.set_wm(w)
        }
        if (object_id(mgrs.md2ampanmda)) {
            w = map.__getitem__(mgrs.gd_gid)
            //printf("%d %d %g\n", mgrs.mitral_gid, mgrs.granule_gid, w)
            mgrs.set_wg(w)
        }
    }
}

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