Classic model of the Tritonia Swim CPG (Getting, 1989)

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Accession:93326
Classic model developed by Petter Getting of the 3-cell core CPG (DSI, C2, and VSI-B) mediating escape swimming in Tritonia diomedea. Cells use a hybrid integrate-and-fire scheme pioneered by Peter Getting. Each model cell is reconstructed from extensive physiological measurements to precisely mimic I-F curves, synaptic waveforms, and functional connectivity. **However, continued physiological measurements show that Getting may have inadvertently incorporated modulatory and or polysynaptic effects -- the properties of this model do *not* match physiological measurements in rested preparations.** This simulation reconstructs the Getting model as reported in: Getting (1989) 'Reconstruction of small neural networks' In Methods in Neural Modeling, 1st ed, p. 171-196. See also, an earlier version of this model reported in Getting (1983). Every attempt has been made to replicate the 1989 model as precisely as possible.
References:
1 . Getting PA (1989) Reconstruction of small neural networks. Methods in Neuronal Modeling: From Synapses to Networks., Koch C:Segev I, ed. pp.171
2 . Getting PA (1983) Mechanisms of pattern generation underlying swimming in Tritonia. II. Network reconstruction. J Neurophysiol 49:1017-35 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Tritonia;
Cell Type(s): Tritonia swim interneuron dorsal; Tritonia cerebral cell; Tritonia swim interneuron ventral;
Channel(s): I A;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Bursting; Oscillations; Invertebrate;
Implementer(s): Calin-Jageman, Robert [rcalinjageman at gsu dot edu];
Search NeuronDB for information about:  I A;
/* 
Written by Bob Calin-Jageman

*/

begintemplate spikehash
	public lastspike, spikehash, ready, stepit, hashvec
	objref cellpointer, hashvec

	proc init() {
		cellpointer = $o1
		hashvec = new Vector()
	}


	proc ready() {
		lastspike = cellpointer.sthold.lastspike
		spikehash = cellpointer.soma.v
	}

	proc stepit() {
		if (lastspike != cellpointer.sthold.lastspike) {
			lastspike = cellpointer.sthold.lastspike
			spikehash = 20-cellpointer.soma.v
		} else {
			spikehash = 0
		}
	}

endtemplate spikehash

objref taptrain, tapfile
taptrain = new Vector()
tapstart = 0

func tapload() {

	taptrain = new Vector()
	tapfile = new File()
	tapfile.ropen($s1)
	while (!tapfile.eof()) {
		taptrain.append(tapfile.scanvar())
	}
	tapfile.close
	
return 1
}



proc readsyn() {localobj synfile
	synfile = new File()
	synfile.ropen($s1)
	

	$o2.G1_weight = synfile.scanvar()
	$o2.G1_eRev = synfile.scanvar()
	$o2.G1_opentc = synfile.scanvar()
	$o2.G1_closetc = synfile.scanvar()

	$o2.G2_weight = synfile.scanvar()
	$o2.G2_eRev = synfile.scanvar()
	$o2.G2_opentc = synfile.scanvar()
	$o2.G2_closetc = synfile.scanvar()

	$o2.G3_weight = synfile.scanvar()
	$o2.G3_eRev = synfile.scanvar()
	$o2.G3_opentc = synfile.scanvar()
	$o2.G3_closetc = synfile.scanvar()

}



/* simulation parameters */

load_file("nrngui.hoc")

// Directory structure reorganized from below to where instead
// the mod files are in the top level directory and multiplatform
// compatible running is documented in the readme.txt
// chdir("c:/sims/ngetting")
// chdir("mods")
// nrn_load_dll("nrnmech.dll")
// chdir("..")

load_file("oldsim/C2Type.hoc") 
load_file("oldsim/DSIType.hoc")
load_file("oldsim/VSIType.hoc")
load_file("oldsim/IFType.hoc")

objref C2, DSI, VSI, IF
C2 = new C2Type()
DSI = new DSIType()
VSI = new VSIType()
IF = new IFType()


load_file("oldsim/struct.hoc")
readsyn("syndefs/ORAMP_DSI.txt", IF_DSIs)
readsyn("syndefs/OC2_DSI.txt", C2_DSIs)
readsyn("syndefs/OVSI_DSI.txt", VSI_DSIs)
readsyn("syndefs/OVSI_C2.txt", VSI_C2s)
readsyn("syndefs/ODSI_C2.txt", DSI_C2s)
readsyn("syndefs/ODSI_VSI.txt", DSI_VSIs)
readsyn("syndefs/OC2_VSI.txt", C2_VSIs)
readsyn("syndefs/ODSI_DSI.txt", DSI_DSIs)
readsyn("syndefs/OVSI_VSI.txt", VSI_VSIs)


objref DSIhash, VSIhash, C2hash
DSIhash = new spikehash(DSI)
VSIhash = new spikehash(VSI)
C2hash = new spikehash(C2)

objref DSIv, C2v, VSIv, results

DSIv = new Vector()
C2v = new Vector()
VSIv = new Vector()
DSIv.record(&DSI.soma.v)
C2v.record(&C2.soma.v)
VSIv.record(&VSI.soma.v)
DSIhash.hashvec.record(&DSIhash.spikehash)
C2hash.hashvec.record(&C2hash.spikehash)
VSIhash.hashvec.record(&VSIhash.spikehash)
results = new Vector()



access C2.soma
load_file("ses/oldcpg.ses")

objref celllist, spikelist
celllist = new List()
spikelist = new List()
celllist.append(DSI)
celllist.append(C2)
celllist.append(VSI)


objref stimcon
stimcon = IF_DSInc
stimdelay = 5000
stimrate = 10
stimduration = 1000
x = 0

objref ifreq
ifreq = new Vector()
ifreq.record(&DSI.sthold.freq)



proc init() {
			

			finitialize(v_init)
			fcurrent()
			
			C2.soma.v = -50
			DSI.soma.v = -40
			VSI.soma.v = -55

			print "adding stim: ", stimcon
			if (taptrain.size > 0) {
				for (am = 0; am < taptrain.size; am = am+1) {
				   stimcon.event(taptrain.x[am]+tapstart)
				}
			} else {

				for(x = stimdelay; x < (stimdelay+stimduration); x = x + ((1/stimrate)*1000)) {
					stimcon.event(x)
				}
			}

	
			DSIhash.ready()
			C2hash.ready()
			VSIhash.ready()

		}

proc savefreq() {local x localobj outfile
	outfile = new File()
	outfile.wopen($s1)

	outfile.printf("label:%s\n", "ifreq")
	outfile.printf("%o\n", ifreq.size())

	for(x =0; x < ifreq.size(); x = x + 1) {
			outfile.printf("%f	%f\n", x*dt, ifreq.x[x])
		}
	outfile.close()

}



proc advance() {
	fadvance()
	
	DSIhash.stepit()
	VSIhash.stepit()
	C2hash.stepit()

}

proc saveresults() {local x, y localobj f
	f = new File()
	f.wopen($s3)
	for (x=0; x<$o1.size; x = x +1) {
		y = $o1.x[x]
		if ($o2.hashvec.x[x] > 10) { y = $o2.hashvec.x[x] }
		f.printf("%f	%f\n", dt*x, y)
	}
	f.close()
}



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