icademo.m

含有多种ICA算法的eeglab工具箱

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% run the ICA decomposition using runica.m
%
% Decompose the data using the ICA algorithm
% Specify the baseline vector to be sure that the baselines are zeroed.
%         data       = input data (size(data) = [chans,frames*epochs])
%         frames     = number of data points in each data epoch 
%         basevector = data point vector to use in zeroing baseline 
%
fprintf('Now decompose both epochs at once using the ICA algorithm, runica() ...\n\n');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;

[weights,sphere,activations,bias,signs,lrates] = runica(data);

fprintf('\nDone!\n');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Compute the activation waveforms for the resulting ICA components using icaact.m
%
  datamean = mean(data')';
  activations = icaact(data,weights*sphere,datamean);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Reorder the first 10 components by increasing in-epoch latency to the
% point of maximum variance accounted for. Do not take into account 
% channel 14 in the variance calculation; only use channels 1:13.
%
fprintf('Re-sorting the resulting components by LATENCY ')
fprintf('          using compsort() ...\n\n');
fprintf('Note: runica() orders components by size - comport() not commonly needed!!\n')

% [windex,maxvar,maxframe,maxepoch,maxmap] ...
%                = compsort(data,weights,sphere,datamean, ...
%                                         frames,nlargest,chanlist);

  [windex,maxvar,maxframe,maxepoch,maxmap] = ...
                   compsort(data,weights,sphere,1,...
                                          frames,10,[1:13]);

fprintf('\nDone!\n');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Plot the activation waveforms of all the components 
%        as reordered by compsort()
% Identify the components using the original component numbers.
%
fprintf('Plotting the component activation waveforms using plotdata()')
fprintf('using plotdata() ....\n\n');
figure('Position',pos+3*off); 

  plotdata(activations(windex,:),frames,limits,...
                 'ICA Component Activations', ...
                          windex,0,'(2 conditions)');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Plot the contributions to the first epoch of data by the first reordered 
% 10 ICA components. Superimpose their projections on the original data.
%
fprintf('Plotting contributions of the 1st 10 ICA components ');
fprintf('using plotproj()...\n\n');
figure('Position',pos+4*off); 

%   [projdata] = plotproj(data,weights,compnums, ...
%                            title,limits,chanlist,channames,colors);
 [projdata] = plotproj(data(:,1:frames),weights*sphere,windex(1:10), ...
               'First epoch (comps. 1-10)',limits,[1:10], chan_locs2 );

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Plot the contributions to the first epoch of data by the 5 largest
% ICA components. Superimpose their projections on the original data.
%
fprintf('Plotting contributions of the 5 largest ICA components ');
fprintf('(windex order) using projtopo()...\n\n');
figure('Position',pos+4*off); 

%       >> [projdata] = projtopo(data,weights,[compnums],chan_locs,...
%                                 'title',[limits],colors,chans);

 [projdata] = projtopo(data(:,1:frames),weights*sphere,1:5,chan_locs,...
               'First epoch',limits);

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Plot the envelopes of the data epoch 1 and the first 10 components
%
fprintf('Plotting the [min,max] "envelopes" of the data ');
fprintf('and largest 6 components using envproj().\n(Data envelope is in white).\n\n');
figure('Position',pos+5*off); 

% >> [envdata] = envproj(data,weights,compnums, ...
%                        title,limits,chanlist,compnames,colors);
  [envdata] = envproj(data(:,1:floor(0.6*frames)),weights*sphere,1:6, ...
                  'Envelopes of data and largest 6 components (cond. 1)',...
                     [0 995*0.6 0 0]);

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
fprintf('Now plotting envelopes PLUS scalp maps using envtopo().\n');
figure('Position',pos+5.5*off); 
%
%  >> envtopo(data,weights,chan_locs,[limits],[compnums],...
%                                   'title',[plotchans],[voffsets]);

  envtopo(data(:,1:floor(0.6*frames)),weights*sphere,'chanlocs',chan_locs,...
         'limits', [0 995*0.6],'compnums',[2 3 4 6],'title', 'Largest Components');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Plot a close-up of the decomposition of epoch 2, channel 2.
% Focus on the time interval 250 to 400 msec.
%
  startframe = fix(0.250*srate)+1; % start 250 msec after epoch start
  endframe   = fix(0.400*srate);   % end 400 msec after epoch start

fprintf('Plotting contributions of the 1st 5 ICA components ');
fprintf('at Cz using chanproj().\nData is in white.\n\n');
figure('Position',pos+6*off); 

% [chandata] = chanproj(projdata,chan,ncomps,framelist,limits,titl,clrs);

  [chandata] = chanproj(projdata,1,5,startframe:endframe,...
                                 [0 995 0 0],'Epoch 1, channel Fz',0);
fprintf('\n Note that two components make up most of the response peak.\n');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Plot the scalp maps of the first four reordered components 
% Read the electrode location file chan_locs
%
fprintf('Plotting 1st 4 ICA component scalp maps using compmap()...\n');
figure('Position',pos+7*off); 

% compmap (winv,eloc_file,index,title,pagesize,labels,printflag)
  compmap(maxmap,chan_locs,1:4,'Maps of 1st 4 ICA Components',...
                                                   [2 2],windex(1:4));

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Display the projected epoch-1 data for reordered ICA component windex(7) 
% together with a scalp map at its point of max variance
%
fprintf('Plotting the scalp maps and 1st-epoch projection of\n');
fprintf('   the button press component using compplot()...\n\n');
figure('Position',pos+8*off); 

% compplot(data,plotframe,chan_file,xstart,srate,title);

  frame = maxframe(7);
  projp3 = icaproj(data(:,frames+1:2*frames),weights*sphere,windex(7));

  compplot(projp3,frame,chan_locs,0,srate,'ICA Button Press Component');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Make and display a brief movie of a small segment of the first data epoch
%
fprintf('Making a brief movie of an N200 portion of the 1st data epoch\n')
fprintf('            using eegmovie() & seemovie()...\n\n');
figure('Position',pos+9*off); 

% [Movie,Colormap] = eegmovie(data,srate,elec_locs,title,movieframes,minmax);

try,
  [Movie,Colormap] = eegmovie(data(:,313:412),srate,chan_locs,...
                                              'Demo of eegmovie()',75:85,0);
% Display the movie slowly, then 5 times forward/back
%
  seemovie(Movie,-5,Colormap); 
catch,
    disp('Problem generating movie');
end;

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
end;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Run testica script using optimum parameters 
%    (nsources = ncomponents to separate)
% Sources are super-Gaussian 
%
fprintf('Last, running testica() - a simulation script for estimating the accuracy\n')
fprintf('         of ICA separation for a given data size and source distribution ...\n\n');

fprintf('Perfect separation would produce an identity matrix.\n');
fprintf('This is not possible here, since 14 sources are mixed into only 6 channels.\n');
fprintf('The figure will show that the 6 largest sources are still recovered clearly ...\n');

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%
    testica(chans,epochs*frames,14,-0.05,1.4);
else 
    [testresult] = testica(chans,epochs*frames,14,-0.05,1.4);
end;

% model 14 sources with a wide range of sizes & positive kurtosis

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

set(gcf,'Position',pos+10*off); 

if ~exist('icademoauto')
    fprintf('\n****> Hit any key to continue: '); pause; fprintf('\n\n'); %%%    
end; 
fprintf('\n *************************************************************\n');
fprintf(' *               For a tutorial on the toolbox:                *\n');
fprintf(' *                                                             *\n');
fprintf(' *          http://www.cnl.salk.edu/~scott/tutorial/           *\n');
fprintf(' *                                                             *\n');
fprintf(' *      For an overview of available scripts  >> help ica      *\n');
fprintf(' *      For information about using ICA, see  icafaq.html      *\n');
fprintf(' *      For further details and examples, see icabib.html      *\n');
fprintf(' *************************************************************\n\n')

return