Grid cell model with compression effects (Raudies & Hasselmo, 2015)

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Accession:194881
We present a model for compression of grid cell firing in modules to changes in barrier location.
Reference:
1 . Raudies F, Hasselmo ME (2015) Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex. PLoS Comput Biol 11:e1004596 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism: Entorhinal cortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Grid cell;
Implementer(s): Raudies, Florian [florian.raudies at gmail.com];
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RaudiesHasselmo2015
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README.html
attractorModel.m
errorarea.m
estimatePosition.m
estimateVelocity.m
Fig2.m
Fig3.m
Fig4.m
FigS1.m
FigS3.m
gpl-3.0.txt *
gridScoreForActivity.m
gridScoreForSpikes.m
ModuleModel.m
randomTrajectory.m
rescaleCorr.m
SimConfA.m
SimConfA.mat
SimConfB.m
SimConfB.mat
SimNoiseWithBias.m
SimNoiseWoutBias.m
TestEstimatePosition.m
vcoModel.m
                            
function [ha hl] = errorarea(X,LineVal,AreaVal,colorArea,colorLine)
% ERRORAREA
%   X               - abscissa.
%   LineVal         - Mean values.
%   AreaVal         - Standard deviation.
%   colorArea       - color of area.
%   colorLine       - color of line.
%
% RETURN
%   ha              - Handle to area.
%   hl              - Handle to line.
%

%   Florian Raudies, 2009/10/23, University of Ulm.

if nargin<4, colorArea='b'; end
if nargin<5, colorLine='k'; end

d = 1;
X = X(:);
LineVal = LineVal(:);
AreaVal = AreaVal(:);

Xd = [X; flipud(X)];
Yd = [LineVal-d*AreaVal; flipud(LineVal+d*AreaVal)];

ha = fill(Xd,Yd,colorArea,'LineStyle','none');
hold on;
hl = plot(X,LineVal,'-','LineWidth',1.0,'Color',colorLine);
hold off;

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