Network recruitment to coherent oscillations in a hippocampal model (Stacey et al. 2011)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:135903
"... Here we demonstrate, via a detailed computational model, a mechanism whereby physiological noise and coupling initiate oscillations and then recruit neighboring tissue, in a manner well described by a combination of Stochastic Resonance and Coherence Resonance. We develop a novel statistical method to quantify recruitment using several measures of network synchrony. This measurement demonstrates that oscillations spread via preexisting network connections such as interneuronal connections, recurrent synapses, and gap junctions, provided that neighboring cells also receive sufficient inputs in the form of random synaptic noise. ..."
Reference:
1 . Stacey WC, Krieger A, Litt B (2011) Network recruitment to coherent oscillations in a hippocampal computer model. J Neurophysiol 105:1464-81 [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): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA3 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; Hippocampus CA1 basket cell;
Channel(s): I Na,t; I A; I K; I h;
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Oscillations;
Implementer(s): Lazarewicz, Maciej [mlazarew at gmu.edu]; Stacey, William [wstacey at med.umich.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; Hippocampus CA3 pyramidal GLU cell; Hippocampus CA1 interneuron oriens alveus GABA cell; GabaA; AMPA; NMDA; I Na,t; I A; I K; I h;
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//
// NOTICE OF COPYRIGHT AND OWNERSHIP OF SOFTWARE
//
// Copyright 2010, The University Of Michigan
// 	
//   All rights reserved.
//   For research use only; commercial use prohibited.
//   No Distribution without permission of William Stacey
//   wstacey@umich.edu
//
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

// Definition of the cellular properties in the network
begintemplate CellParam

public name, N, iappSl, iappSh, iappSsd, iappAl, iappAh, iappAsd, iappUnits 

strdef name

proc init() {
	
	name      = $s1// Name of the cell, e.g. Pyr
	N         = $2 // Number of the cells in the network
	iappSl    = $3 // The lowest value for the somatic injected curreent (over the population)
	iappSh    = $4 // The highest value for the somatic injected curreent (over the population)
	iappSsd   = $5 // Standard Deviation of the somatic injected curreent (for one cell)
	iappAl    = $6 // apical
	iappAh    = $7 // apical
	iappAsd   = $8 // apical
	iappUnits = $9 // Units 0-pA 1-uA/cm2
	
	//print $s1, $2, $3, $4, $5, $6, $7, $8, $9
}

endtemplate CellParam

// TEMPLATE
begintemplate CellParamSet

public cellSet
objref cellSet
strdef name, tmpstr, tmpstr2

proc init() { local N localobj fo, strFun

	N         = 0	
	iappSl    = 0
	iappSh    = 0
	iappSsd   = 0
	iappAl    = 0
	iappAh    = 0
	iappAsd   = 0
	iappUnits = 0
	
	cellSet  = new List()
	strFun   = new StringFunctions()
	
	// READ cells
	fo = new File("parameters/cells.par")
	fo.ropen()
	
	while(!fo.eof()) {
	
		fo.gets(tmpstr)
		
		// Find in tmpstr all that follows non-blank character, and store it in tmpstr2
		strFun.tail(tmpstr, "[^\t]", tmpstr2)
		
		// Remove end of the line
		strFun.head(tmpstr2, "\n", tmpstr2)
		
		// Process data if nonepty line
		if (strFun.len(tmpstr2)>0 && strFun.substr(tmpstr, "//")==-1) {
			
			sscanf(tmpstr, "%[^,], %d, %lf, %lf, %lf, %lf, %lf, %lf, %d\n", name, &N,	&iappSl, &iappSh, &iappSsd, &iappAl, &iappAh, &iappAsd, &iappUnits)
			cellSet.append(new CellParam( name, N, iappSl, iappSh, iappSsd, iappAl, iappAh, iappAsd, iappUnits) )
		}
	}
		
	fo.close()
}
	
endtemplate CellParamSet

Loading data, please wait...