% std_dipoleclusters - Plots clusters of ICs as colored dipoles in MRI
% images (side, rear, top and oblique angles possible)
%
% std_dipoleclusters(STUDY,ALLEEG,'key1',value1, 'key2',value2, ... );
%
% Inputs:
% STUDY - EEGLAB STUDY set
% ALLEEG - vector of the EEG datasets included in the STUDY structure
%
% Optional inputs:
% 'clusters' - [vector of numbers] list of clusters to plot in same head space
% 'title' - [string] figure title
% 'viewnum' - [vector] list of views to plot: 1=top, 2=side, 3=rear, 4 is an oblique view;
% length(viewnum) gives the number of subplots that will be produced and the
% values within the vector tell the orientation and order of views
% 'rowcolplace' - [rows cols subplot] If plotting into an existing figure, specify the number of rows,
% columns and the subplot number to start plotting dipole panels.
% 'colors' - [vector or matrix] if 1 x 3 vector of RGB values, this will plot all dipoles as the
% same color. ex. [1 0 0] is red, [0 0 1] is blue, [0 1 0] is green.
% If a matrix, should be n x 3, with the number of rows equal to the number
% of clusters to be plotted and the columns should be RGB values for each.
% If [], will plot clusters as 'jet' colorscale from the first to the last cluster
% requested (therefore an alternate way to control dipole color is to input a specific
% order of clusters).
% [] will assign colors from hsv color scale.
% 'centroid' - ['only', 'add', 'off'] 'only' will plot only cluster centroids, 'add' will superimpose
% centroids over cluster dipoles, 'off' will skip centroid plotting and only plot
% cluster-member dipoles.
%
% Authors: Julie Onton, SCCN/INC UCSD, June 2009
% Copyright (C) Julie Onton, SCCN/INC/UCSD, October 11, 2009
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
%
% 1. Redistributions of source code must retain the above copyright notice,
% this list of conditions and the following disclaimer.
%
% 2. Redistributions in binary form must reproduce the above copyright notice,
% this list of conditions and the following disclaimer in the documentation
% and/or other materials provided with the distribution.
%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
% THE POSSIBILITY OF SUCH DAMAGE.
function std_dipoleclusters(STUDY,ALLEEG, varargin);
if nargin < 2
help std_dipoleclusters;
return;
end
% Set default values------------------------------------------------------------------------
if strcmp(STUDY.cluster(2),'outlier 2') % don't plot outlier cluster #2
clustvec = [3:length(STUDY.cluster)]; % plot all clusters in STUDY
else
clustvec = [2:length(STUDY.cluster)]; % plot all clusters in STUDY
end
onecolor = [];
colvec = [];
centroid = 'off';
viewnum = [1:4]; % plot all views and oblique
rowcolplace = [2 2 1]; % 2 X 2 figure starting in subplot 1
figureon = 1; % plot on a new figure
ttl = ''; % no title
%---------------------------------------------------------------------------------
for k = 3:2:nargin
switch varargin{k-2}
case 'clusters'
clusters = varargin{k-1}; % redefine from all to specified clusters
case 'title'
ttl = varargin{k-1};
case 'viewnum',
viewnum = varargin{k-1};
case 'rowcolplace' %, mode = varargin{k-1}; % what is mode? JO
rowcolplace = varargin{k-1};
if length(rowcolplace) < 3
fprintf('\nThe variable ''rowcolplace'' must contain 3 values.\n');
return;
end
row = rowcolplace(1);
col = rowcolplace(2);
place = rowcolplace(3);
figureon = 0; % don't pop a new figure if plotting into existing fig
case 'colors'
colvec = varargin{k-1};
case 'centroid'
centroid = varargin{k-1};
end
end
% adjust color matrix for dipoles:---------------
if isempty(colvec)
cols = jet(length(clusters));% default colors
else
cols = colvec; % input RGB colors
end;
% extract IC cluster and data path info from STUDY structure
clear clustcps fullpaths gdcomps
x = cell(1,length(unique({STUDY.datasetinfo.subject})));
subjs = unique_bc({STUDY.datasetinfo.subject});
origlist = cell(1,length(unique({STUDY.datasetinfo.subject})));
sets = cell(1,length(unique({STUDY.datasetinfo.subject})));
for clust = 1:length(STUDY.cluster)
clustcps{clust} = x;
for st = 1:size(STUDY.cluster(clust).sets,2)
currset = STUDY.cluster(clust).sets(1,st);
currcomp = STUDY.cluster(clust).comps(1,st);
subjidx = strmatch(STUDY.datasetinfo(currset).subject,subjs);
clustcps{clust}{subjidx}(end+1) = currcomp;
origlist{subjidx} = [origlist{subjidx} currcomp];
[origlist{subjidx} idx] = unique_bc(origlist{subjidx});
sets{subjidx} = currset;
end;
end
%-----------------------------------------------------------
% extract dipole info for ALL ICs to be plotted subj by subj
for nx = 1:length(origlist)
dipsources = [];
if ~isempty(origlist{nx})
EEG = ALLEEG(sets{nx}); % call in a dataset from subj
if isfield(EEG.dipfit.model,'diffmap')
EEG.dipfit.model = rmfield(EEG.dipfit.model,'diffmap');
end
if isfield(EEG.dipfit.model,'active')
EEG.dipfit.model = rmfield(EEG.dipfit.model,'active');
end
if isfield(EEG.dipfit.model,'select')
EEG.dipfit.model = rmfield(EEG.dipfit.model,'select');
end
dipsources.posxyz = EEG.dipfit.model(origlist{nx}(1)).posxyz;
dipsources.momxyz = EEG.dipfit.model(origlist{nx}(1)).momxyz;
dipsources.rv = EEG.dipfit.model(origlist{nx}(1)).rv;p=1;
for w = 1:length(origlist{nx})
dipsources(1,p).posxyz = EEG.dipfit.model(origlist{nx}(w)).posxyz;
dipsources(1,p).momxyz = EEG.dipfit.model(origlist{nx}(w)).momxyz;
dipsources(1,p).rv = EEG.dipfit.model(origlist{nx}(w)).rv;
p=p+1;
end
allbesa1{nx} = dipsources; new = 0;
end
end;
%-----------------------------------------------------------
% collect cluster dipole info from extracted dipole infos (above)
%%%%%%%%%%%%%%%%%%%%%%%%%
new = 1; pp=1; bic = 1;
centrstr = struct('posxyz',[0 0 0],'momxyz',[0 0 0],'rv',0);
for clst =1:length(clusters)
clust = clusters(clst);
centr = [];
centr2 = [];
for nx = 1:length(clustcps{clust})
if ~isempty(clustcps{clust}{nx})
for k = 1:length(clustcps{clust}{nx})
if new == 1
allbesa = allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k)));
centr = [centr; allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(1,:)];
if size(allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz,1) > 1& allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,1) ~= 0 % actual values, not zero
if allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,2) > 0 % on the wrong side, switch with centr1
centr2 = [centr2;allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,:)];
centr2(end,2) = centr2(end,2)*-1; centr1(end,2) = centr1(end,2)*-1;
else
centr2 = [centr2;allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,:)];
end
end
new = 0;
else
allbesa(1,end+1) = allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k)));
centr = [centr; allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(1,:)];
if size(allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz,1) > 1 && allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,1) ~= 0 % actual values, not zero
if allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,2) > 0 % on the wrong side, switch with centr1
centr2 = [centr2; allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,:)];
centr2(end,2) = centr2(end,2)*-1; centr1(end,2) = centr1(end,2)*-1;
else
centr2 = [centr2;allbesa1{nx}(find(origlist{nx} == clustcps{clust}{nx}(k))).posxyz(2,:)];
end
end
end;
colset{pp} = cols(clst,:); pp = pp+1;
end
end
end
if length(allbesa) > 1
centr = mean(centr,1);
centr2 = mean(centr2,1);
centrstr(clst).posxyz = centr;
centrstr(clst).momxyz = allbesa(end).momxyz(1,:);
centrstr(clst).rv = 2;
centcols{clst} = cols(clst,:);
centcols2{clst} = cols(clst,:)/5;
if ~isempty(find(centr2))
centrstr2(bic).posxyz = centr2;
centrstr2(bic).momxyz = allbesa(end).momxyz(1,:);
centrstr2(bic).rv = 2;
bic = bic + 1; % separate count for bilaterals
end
end
end
if figureon == 1
figure; row = 2; col = 2; place= 1;
end
%-------------------------------------------
% PLOT the clusster dipoles:
if length(allbesa) > 1
for sbpt = 1:length(viewnum)
if sbpt < 4
prjimg = 'off';
else
prjimg = 'on';
end
sbplot(row,col,place)
if strcmp(centroid,'only')
dipplot(centrstr,'image','mri','gui','off','dipolelength',0,'dipolesize',40,'normlen','on','spheres','on','color',centcols,'projlines','off','projimg',prjimg,'coordformat',EEG.dipfit.coordformat);hold on; view(90,0);
if ~isempty(find(centrstr2(1).posxyz)) % only if there were bilaterals
dipplot(centrstr2,'image','mri','gui','off','dipolelength',0,'dipolesize',40,'normlen','on','spheres','on','color',centcols,'projlines','off','projimg',prjimg,'coordformat',EEG.dipfit.coordformat);hold on; view(90,0); camzoom(.8)
else
camzoom(1)
end
elseif strcmp(centroid,'add')
dipplot(allbesa,'image','mri','gui','off','dipolelength',0,'dipolesize',25,'normlen','on','spheres','on','color',colset,'projlines','off','projimg',prjimg,'coordformat',EEG.dipfit.coordformat);hold on; view(90,0);
dipplot(centrstr,'image','mri','gui','off','dipolelength',0,'dipolesize',40,'normlen','on','spheres','on','color',centcols2,'projlines','off','projimg',prjimg,'coordformat',EEG.dipfit.coordformat);hold on; view(90,0); camzoom(.8)
if ~isempty(find(centrstr2(1).posxyz)) % only if there were bilaterals
dipplot(centrstr2,'image','mri','gui','off','dipolelength',0,'dipolesize',40,'normlen','on','spheres','on','color',centcols2,'projlines','off','projimg',prjimg,'coordformat',EEG.dipfit.coordformat);hold on; view(90,0);camzoom(.8)
else
camzoom(1)
end
else
dipplot(allbesa,'image','mri','gui','off','dipolelength',0,'dipolesize',25,'normlen','on','spheres','on','color',colset,'projlines','off','projimg',prjimg,'coordformat',EEG.dipfit.coordformat);hold on; view(90,0); camzoom(1.1)
end
if viewnum(sbpt) == 3
view(0,0)
elseif viewnum(sbpt) == 1
view(0,90)
elseif viewnum(sbpt) == 4
view(63,22);
end
place = place+1;
end;
if ~isempty(ttl)
if sbpt == 4 % if oblique
ph = text(-75,-75,125,ttl); set(ph,'color','r');
elseif sbpt == 1 % 2d image:
ph = text(-50,110,125,ttl); set(ph,'color','r');
elseif sbpt == 2 % 2d image:
ph = text(-75,-75,125,ttl); set(ph,'color','r');
elseif sbpt == 3 % 2d image:
ph = text(-100,-50,130,ttl); set(ph,'color','r');
end
end
end
Datasets
Models
