Role for short term plasticity and OLM cells in containing spread of excitation (Hummos et al 2014)

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Accession:168314
This hippocampus model was developed by matching experimental data, including neuronal behavior, synaptic current dynamics, network spatial connectivity patterns, and short-term synaptic plasticity. Furthermore, it was constrained to perform pattern completion and separation under the effects of acetylcholine. The model was then used to investigate the role of short-term synaptic depression at the recurrent synapses in CA3, and inhibition by basket cell (BC) interneurons and oriens lacunosum-moleculare (OLM) interneurons in containing the unstable spread of excitatory activity in the network.
References:
1 . Hummos A, Franklin CC, Nair SS (2014) Intrinsic mechanisms stabilize encoding and retrieval circuits differentially in a hippocampal network model. Hippocampus 24:1430-48 [PubMed]
2 . Hummos A, Nair SS (2017) An integrative model of the intrinsic hippocampal theta rhythm. PLoS One 12:e0182648 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Dentate gyrus granule GLU cell; Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; Hippocampus CA3 stratum oriens lacunosum-moleculare interneuron; Abstract Izhikevich neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Acetylcholine; Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Epilepsy; Storage/recall;
Implementer(s):
Search NeuronDB for information about:  Dentate gyrus granule GLU cell; Hippocampus CA3 pyramidal GLU cell; Hippocampus CA3 interneuron basket GABA cell; Acetylcholine; Gaba; Glutamate;
		/////// Recording variables//////////////
// recording membrane voltage
objref Volts, vvec, tvvec, CellsToRec
Volts = new List()
CellsToRec = new Vector()
CellsToRec.indgen(0,61,1)

	tvvec = new Vector()
	tvvec.record(&t)
	//Volts.append(tvvec)
	
for y = 0, CellsToRec.size() -1 {
	vvec = new Vector()
	
	vvec.record(&Cells.o(1).o( CellsToRec.x(y) ).soma.v(0.5))

	Volts.append(vvec)
}


// Recording weights
objref Weights, WeightTimes, wvec, twvec
Weights = new List()
WeightTimes = new List()
twvec = new Vector()

twvec.record(&t, 40)

for s = 0, Syn.count() -1 {
	wvec = new Vector()

	if (Connections.x(s, 5) == 1 || Connections.x(s, 5) == 3) {
		wvec.record(&Syn.o(s).W_ampa, 40)//, twvec,1)
		} else {
			if (Connections.x(s,5) == 0 || Connections.x(s, 5) == 2) {
				wvec.record(&Syn.o(s).W_gabaa, 40)///, wvec, twvec,1)
			} else {
			printf("\n ----------- Problem finding connection to record\n")
			}
		}		
Weights.append(wvec)
} // for s

// Recording Currents
objref Currents, rectvec, cvec, twvec1
twvec1 = new Vector()
Currents = new List()
rectvec = new Vector()

// for (i = StimSpace * 5; i <= StimSpace * 6; i+=5) {
	// rectvec.append(i)
// }
		rectvec.indgen(StimSpace * 0, StimSpace * (StimCount ), StimSpace/130 )
		twvec1 = rectvec 
for s = 0, Syn.count() -1 {
	cvec = new Vector()

	if (Connections.x(s, 5) == 1 || Connections.x(s, 5) == 3) {
	// cvec.record(&Syn.o(s).D1, twvec1,1)
		cvec.record(&Syn.o(s).i_ampa, twvec1,1)
		// cvec.record(&Syn.o(s).Capoolcon, 40)//, twvec,1)
		} else {
			if (Connections.x(s,5) == 0 || Connections.x(s, 5) == 2) {
				cvec.record(&Syn.o(s).i_gabaa, twvec1,1)
				// cvec.record(&Syn.o(s).Capoolcon, 40)///, wvec, twvec,1)
			} else {
			printf("\n ----------- Problem finding connection to record\n")
			}
		}		
Currents.append(cvec)
} // for s

// Recording Spike times
objref SpikeIDs, SpikeTimes, Sidvec, Stvec, nc_, nil
SpikeIDs = new List()
SpikeTimes = new List()

for c = 0, Cells.count() - 1 {
	Sidvec = new Vector()
	Stvec = new Vector()
	for ii = 0, Cells.o(c).count() - 1 {
		Cells.o(c).o(ii).soma nc_ = new NetCon(&v(0.5), nil)
		nc_.threshold = -20
		nc_.record(Stvec, Sidvec, ii)
	}
	SpikeIDs.append(Sidvec)
	SpikeTimes.append(Stvec)
}

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