Model of memory linking through memory allocation (Kastellakis et al. 2016)

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Here, we present a simplified, biophysically inspired network model that incorporates multiple plasticity processes and explains linking of information at three different levels: (a) learning of a single associative memory (b) rescuing of a weak memory when paired with a strong one and (c) linking of multiple memories across time. By dissecting synaptic from intrinsic plasticity and neuron-wide from dendritically restricted protein capture, the model reveals a simple, unifying principle: Linked memories share synaptic clusters within the dendrites of overlapping populations of neurons
1 . Kastellakis G, Silva AJ, Poirazi P (2016) Linking Memories across Time via Neuronal and Dendritic Overlaps in Model Neurons with Active Dendrites. Cell Rep 17:1491-1504 [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:
Cell Type(s): Abstract integrate-and-fire leaky neuron with dendritic subunits;
Gap Junctions:
Simulation Environment: C or C++ program; C or C++ program (web link to model);
Model Concept(s): Active Dendrites;
Implementer(s): Kastellakis, George [gkastel at];
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%COPYFIG Create a copy of a figure, without changing the figure
% Examples:
%   fh_new = copyfig(fh_old)
% This function will create a copy of a figure, but not change the figure,
% as copyobj sometimes does, e.g. by changing legends.
% IN:
%    fh_old - The handle of the figure to be copied. Default: gcf.
% OUT:
%    fh_new - The handle of the created figure.

% Copyright (C) Oliver Woodford 2012

function fh = copyfig(fh)
% Set the default
if nargin == 0
    fh = gcf;
% Is there a legend?
if isempty(findall(fh, 'Type', 'axes', 'Tag', 'legend'))
    % Safe to copy using copyobj
    fh = copyobj(fh, 0);
    % copyobj will change the figure, so save and then load it instead
    tmp_nam = [tempname '.fig'];
    hgsave(fh, tmp_nam);
    fh = hgload(tmp_nam);