Model of arrhythmias in a cardiac cells network (Casaleggio et al. 2014)

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Accession:150691
" ... Here we explore the possible processes leading to the occasional onset and termination of the (usually) non-fatal arrhythmias widely observed in the heart. Using a computational model of a two-dimensional network of cardiac cells, we tested the hypothesis that an ischemia alters the properties of the gap junctions inside the ischemic area. ... In conclusion, our model strongly supports the hypothesis that non-fatal arrhythmias can develop from post-ischemic alteration of the electrical connectivity in a relatively small area of the cardiac cell network, and suggests experimentally testable predictions on their possible treatments."
Reference:
1 . Casaleggio A, Hines ML, Migliore M (2014) Computational model of erratic arrhythmias in a cardiac cell network: the role of gap junctions. PLoS One 9:e100288 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Cardiac ventricular cell;
Channel(s): I K; I Sodium; I Calcium; I Potassium;
Gap Junctions: Gap junctions;
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Spatio-temporal Activity Patterns; Detailed Neuronal Models; Action Potentials; Heart disease; Conductance distributions;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu]; Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  I K; I Sodium; I Calcium; I Potassium;
// utility functions to convert (Nx, Ny) to gid and also the
// gap junction indices.

func loc2gid() { local gid
	// because of different boundary conditions we want to properly
	// handle x and y locations of -1 and Nx, and Ny respectively
	// return -1 if the location is not in the domain
	$1 = bndry($1, Nx, xwrap)
	if ($1 < 0) { return -1 }
	$2 = bndry($2, Ny, ywrap)	
	if ($2 < 0) { return -1 }
	return $1 + $2*Nx
}
func bndry() {
	if ($3 == 1) { // wrap
		if ($1 < -1) { return -1 }
		if ($1 == -1) { return $2-1 }
		if ($1 > $2) { return -1 }
		if ($1 == $2) { return 0 }
	}else if ($3 == 2) { // mirror
		if ($1 < -1) { return -1 }
		if ($1 == -1) { return 1 }
		if ($1 > $2) { return -1 }
		if ($1 == $2) { return $2-2 }
	}else{ // cut
		if ($1 < 0) { return -1 }
		if ($1 >= $2) { return -1 }
	}
	return $1
}
func gid2ix() {
	return $1 % Nx
}
func gid2iy() {
	return int($1/Nx)
}

// each cell has 4 gap junction targets and the cell voltage is the
// source for a target on each of the 4 adjacent cells.
// Since the assumption is one compartment per cell we can use the
// cell gid as the transfer srcgid. If cells become multicompartment
// this conceptual strategy will have to drastically change.

// what is the gap srcgid for a given cell location
func gapsrcgid() {
	return loc2gid($1, $2)
}
// Note that for a target (x,y) cell's HalfGaps we are interested in
// the gapsrcgid for the four sources (x+1, y), (x-1, y), (x, y+1), (x, y-1)
// whose global existence depends on the kind of boundary condition selected.

// given a cell gid and a gap index (0-3) for the half gaps associated
// with that cell, what is the gid of the cell
// that provides the spike to the gap for the purpose of randomly changing
// the conductance of the gap. Note it is critical for each side of a gap
// to get the same spikes. Cell gid provides spikes to the left and upper
// pair of gaps relative to that cell.
func gapspkgid() {
	if ($2 == 0) { // right
		return $1
	}else if ($2 == 1) { // upper
		return $1
	}else if ($2 == 1) { // left
		return loc2gid(gid2ix($1)-1, gid2iy($1))
	}else { // lower
		return loc2gid(gid2ix($1), gid2iy($1)-1)
	}
}