Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells (Lee et al. 2014)

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This detailed microcircuit model explores the network level effects of sublayer specific connectivity in the mouse CA1. The differences in strengths and numbers of synapses between PV+ basket cells and either superficial sublayer or deep sublayer pyramidal cells enables a routing of inhibition from superficial to deep pyramidal cells. At the network level of this model, the effects become quite prominent when one compares the effect on firing rates when either the deep or superficial pyramidal cells receive a selective increase in excitation.
1 . Lee SH, Marchionni I, Bezaire M, Varga C, Danielson N, Lovett-Barron M, Losonczy A, Soltesz I (2014) Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells. Neuron 82:1129-44 [PubMed]
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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 basket cell;
Channel(s): I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Connectivity matrix; Laminar Connectivity;
Implementer(s): Bezaire, Marianne [mariannejcase at];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; Glutamate; I Sodium; I Calcium; I Potassium;
begintemplate RandomStream
	public r, repick, start, rseed, seq	// Define variables and funcs that are
									//  accessible from outside the class
									//  object
	objref r						// Define a new object
	proc init() {					// Define an init proc that runs whenever
									//  a new member of the RandomStream
									//  class is instantiated
		startseed = $1				// Arg 1 specifies where in this
									//  cell's randomstream to start
		rseed = $2					// Arg 2 specifies which randomstream
									//  to use (based on the gid of the cell)
		r = new Random()			// Set the object r to a Random object
		start()						// Run the 'start' func (defined below)
									//  on this newly created RandomStream
	func start() {					// Define a 'start' func for this class

		return r.MCellRan4(startseed, rseed)
									// The function returns with a random
									//  number obtained using the MCellRan4
									//  algorithm, with the seed based on
									//  the gid of this cell as the
									//  starting point for the low index.
									//  The high index will start after
									//  a section reserved for cell noise 
	func repick() {					// Define a 'repick' func for this class
		return r.repick()			// Subsequent random numbers are picked
									//  from this random number stream
	func seq() {
		return r.seq()
endtemplate RandomStream