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CA1 pyramidal neuron (Combe et al 2018)

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Accession:244416
"Gamma oscillations are thought to play a role in learning and memory. Two distinct bands, slow (25-50 Hz) and fast (65-100 Hz) gamma, have been identified in area CA1 of the rodent hippocampus. Slow gamma is phase-locked to activity in area CA3 and presumably driven by the Schaffer collaterals. We used a combination of computational modeling and in vitro electrophysiology in hippocampal slices of male rats to test whether CA1 neurons responded to Schaffer collateral stimulation selectively at slow gamma frequencies, and to identify the mechanisms involved. Both approaches demonstrated that in response to temporally precise input at Schaffer collaterals, CA1 pyramidal neurons fire preferentially in the slow gamma range regardless of whether the input is at fast or slow gamma frequencies, suggesting frequency selectivity in CA1 output with respect to CA3 input. In addition, phase-locking, assessed by the vector strength, was more precise for slow gamma than fast gamma input. ..."
Reference:
1 . Combe CL, Canavier CC, Gasparini S (2018) Intrinsic Mechanisms of Frequency Selectivity in the Proximal Dendrites of CA1 Pyramidal Neurons. J Neurosci 38:8110-8127 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Gamma oscillations;
Implementer(s): Canavier, CC;
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium;
objref sr,k
objref matrix_coord,vector_L 
objref TP_list



//----------------------	Tip_sections()	----------------------------------
//Outputs:	matrix_coord is the a matrix with TP coord.
//		TP_list is a list with the TP sections 
//		vector_L is a vector with the lenght of the Terminal section
//		num_tips is the number of Tips
//Inputs:	$o1 is object type SectionList() where are dendrites (or apical dendrites) sections
//		$o2 is object type SectionList() where are soma (or trunk) sections
//		$s3 is a string where has "Dendrites" or "Apical dendrites"
objref jo
proc Tip_sections(){local i, nrow
	i=0
	nrow=1
	matrix_coord = new Matrix(nrow,3)
	TP_list = new SectionList()
	vector_L=new Vector(nrow)

	strdef tmp_str, tmp_str2

	forsec $o1{	
		sr=new SectionRef()
		if (sr.nchild==0) {
		
			secname() TP_list.append()

			matrix_coord.resize(nrow,3)
			matrix_coord.x[nrow-1][0]=x3d(n3d()-1)
			matrix_coord.x[nrow-1][1]=y3d(n3d()-1)
			matrix_coord.x[nrow-1][2]=z3d(n3d()-1)
			
			vector_L.resize(nrow)
			vector_L.x[nrow-1]=L

			nrow+=1
		
		}
	}
//	TP_list.printnames()
	nrow-=1
	print "\nNumber of Terminal Point in ",$s3,": ", nrow, "\n"

	num_tips=nrow

}


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