Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012)

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There is suggestive evidence that pyramidal cell axons in neocortex may be coupled by gap junctions into an ``axonal plexus" capable of generating Very Fast Oscillations (VFOs) with frequencies exceeding 80 Hz. It is not obvious, however, how a pyramidal cell in such a network could control its output when action potentials are free to propagate from the axons of other pyramidal cells into its own axon. We address this problem by means of simulations based on 3D reconstructions of pyramidal cells from rat somatosensory cortex. We show that somatic depolarization enables propagation via gap junctions into the initial segment and main axon, while somatic hyperpolarization disables it. We show further that somatic voltage cannot effectively control action potential propagation through gap junctions on minor collaterals; action potentials may therefore propagate freely from such collaterals regardless of somatic voltage. In previous work, VFOs are all but abolished during the hyperpolarization phase of slow-oscillations induced by anesthesia in vivo. This finding constrains the density of gap junctions on collaterals in our model and suggests that axonal sprouting due to cortical lesions may result in abnormally high gap junction density on collaterals, leading in turn to excessive VFO activity and hence to epilepsy via kindling.
1 . Munro E, Kopell N (2012) Subthreshold somatic voltage in neocortical pyramidal cells can control whether spikes propagate from the axonal plexus to axon terminals: a model study. J Neurophysiol 107:2833-52 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
Channel(s): I Na,t; I K; I Sodium; I Potassium;
Gap Junctions: Gap junctions;
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Oscillations; Detailed Neuronal Models; Axonal Action Potentials; Epilepsy;
Implementer(s): Munro, Erin [ecmun at];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; I Na,t; I K; I Sodium; I Potassium;
function cluster = conn_clusters(conn)
% give clusters of conn in cell array clusters

sc = length(conn);

cells = 1:sc;
j = 1; % current cluster
while ~isempty(cells)
	cells_left = length(cells);
	cell = cells(1); % take first cell not dealt with
	cells = cells(2:length(cells)); %remove it from list
	cluster{j} = cell; % make a new cluster with it
	ends = conn{cell}; % get its connections
	while ~isempty(ends)
		cluster{j} = [cluster{j} ends]; %add cells to cluster
		% remove ends from cells one at a time
		for k = ends 
			%kend = k
			ki = find(cells == k,1);
			if ki > 1
				front = 1:(ki-1);
			else front = []; end
			if ki < length(cells)
				back = (ki+1):length(cells);
			else back = []; end
			cells = [cells(front) cells(back)];
			cells_left = length(cells);
		%cell_list = cells
		old_ends = ends;
		ends = [];
		for k = old_ends % for all old ends
			% test each cell they're connected to
			for test = conn{k}
				% to see if they're in the cluster or ends
				inclus = find(test == cluster{j},1);
				inends = find(test == ends,1);
				for ci = 1:j-1
					if find(test == cluster{ci})
						error('end in other cluster')
				if isempty(inclus) && isempty(inends)
					ends = [ends test];
		end % k = old_ends
		%new_end = ends
	end % ~isempty(ends)
	% now that all cells in the cluster are added
	% move on to new cluster
	cells_left = length(cells);
	j = j + 1;
end % ~isempty(cells)

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