Hippocampal CA1 NN with spontaneous theta, gamma: full scale & network clamp (Bezaire et al 2016)

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Accession:187604
This model is a full-scale, biologically constrained rodent hippocampal CA1 network model that includes 9 cells types (pyramidal cells and 8 interneurons) with realistic proportions of each and realistic connectivity between the cells. In addition, the model receives realistic numbers of afferents from artificial cells representing hippocampal CA3 and entorhinal cortical layer III. The model is fully scaleable and parallelized so that it can be run at small scale on a personal computer or large scale on a supercomputer. The model network exhibits spontaneous theta and gamma rhythms without any rhythmic input. The model network can be perturbed in a variety of ways to better study the mechanisms of CA1 network dynamics. Also see online code at http://bitbucket.org/mbezaire/ca1 and further information at http://mariannebezaire.com/models/ca1
References:
1 . Bezaire MJ, Raikov I, Burk K, Vyas D, Soltesz I (2016) Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit. Elife [PubMed]
2 . Bezaire M, Raikov I, Burk K, Armstrong C, Soltesz I (2016) SimTracker tool and code template to design, manage and analyze neural network model simulations in parallel NEURON bioRxiv
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): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; Hippocampus CA1 basket cell; Hippocampus CA1 stratum radiatum interneuron; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA1 PV+ fast-firing interneuron;
Channel(s): I Na,t; I K; I K,leak; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s): GabaA; GabaB; Glutamate; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; NEURON (web link to model);
Model Concept(s): Oscillations; Methods; Connectivity matrix; Laminar Connectivity; Gamma oscillations;
Implementer(s): Bezaire, Marianne [mariannejcase at gmail.com]; Raikov, Ivan [ivan.g.raikov at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; GabaA; GabaB; Glutamate; Gaba; I Na,t; I K; I K,leak; I h; I K,Ca; I Calcium; Gaba; Glutamate; 
strdef fn
objref pattern_, tvec_, idvec_
proc gridcellStims() { local i, reli, pci, jgid, celltype, numspikes, numconns, precell, pretype, syntype, postcell, normweight, delay localobj cell, f2		// Connect the perforant path cells to the model cells
	jgid = 619
	if (pc.gid_exists(jgid)) {
		f2 = new File()
		sprint(fn, "./stimvecs/gridconns_%g.dat", jgid)
		//sprint(fn, "./stimulation/stimvecs/gridconns_%g.dat", jgid)
		f2.ropen(fn)
		numconns = f2.scanvar			// # cell types, including 1 for pp cells
		for i=1, numconns {
			precell=f2.scanvar
			postcell=f2.scanvar
			pretype=f2.scanvar
			syntype=f2.scanvar
			normweight=f2.scanvar
			delay=f2.scanvar
			cell = pc.gid2cell(postcell)
			printf("pre=%g post=%g syntype=%g\n", precell, postcell, syntype)
			nc_appendo(precell, cell, 0, syntype, normweight*2e-2, delay+2*dt)
		}
		cellType[0].numCons.x[1] +=numconns
		f2.close()

		pattern_ = new PatternStim()

		f2 = new File()
		//f2.ropen("./stimulation/stimvecs/gc_vec.dat")
		f2.ropen("./stimvecs/gc_vec.dat")
		numspikes = f2.scanvar
		i=f2.scanvar // Don't need this, just a placeholder value
		tvec_ = new Vector(numspikes)
		idvec_ = new Vector(numspikes)

		for i=0, numspikes-1 {
			tvec_.x[i] = f2.scanvar // spike time in ms
			idvec_.x[i] = f2.scanvar // gid of NetStim to make fire
		}
		f2.close()

		pattern_.fake_output = 1
		pattern_.play(tvec_, idvec_)
	}
}
gridcellStims()

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