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spm_eeg_inv_results_display.m
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spm_eeg_inv_results_display.m
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function spm_eeg_inv_results_display(D)
% Displays contrast of evoked responses and power
% FORMAT spm_eeg_inv_results_display((D)
%__________________________________________________________________________
% Copyright (C) 2007-2013 Wellcome Trust Centre for Neuroimaging
% Karl Friston
% $Id: spm_eeg_inv_results_display.m 5367 2013-03-28 13:03:39Z guillaume $
%==========================================================================
Ndip = 256; % Number of dipoles to display
%==========================================================================
%-MEEG data structure
%==========================================================================
try, val = D.val; catch, val = 1; end
try, con = D.con; catch, con = 1; end
if con == 0
con = 1;
end
model = D.inv{D.val};
try
con = min(con,length(model.contrast.GW));
catch
warndlg('please specify a [time-frequency] contrast')
return
end
% inversion parameters
%--------------------------------------------------------------------------
Is = model.inverse.Is; % Indices of ARD vertices
pst = model.inverse.pst; % preistimulus tim (ms)
Nd = model.inverse.Nd; % number of mesh dipoles
Ndip = min(Ndip,length(Is));
try
W = model.contrast.W{con};
catch
W = model.contrast.W;
end
JW = model.contrast.JW{con};
GW = model.contrast.GW{con};
% just display the first trial (for trial-specific contrasts)
%--------------------------------------------------------------------------
if iscell(GW)
GW = GW{1};
end
% sqrt(energy) (G) = abs(JW) for single trials
%--------------------------------------------------------------------------
G = sqrt(sparse(Is,1,GW,Nd,1));
%-Display
%==========================================================================
Fgraph = spm_figure('GetWin','Graphics');
spm_figure('Clear',Fgraph)
spm_figure('Focus',Fgraph)
% get vertices (even if not normalised)
%--------------------------------------------------------------------------
vert = model.mesh.tess_mni.vert;
% display
%--------------------------------------------------------------------------
subplot(2,1,1)
[i,j] = sort(-G);
j = j(1:Ndip);
spm_mip(G(j),vert(j,:)',6);
axis image
try
if strcmp(model.contrast.type, 'trials')
str = sprintf('Energy (%s)', 'first trial');
else
str = sprintf('Energy (%s)', model.contrast.type);
end
catch
str = 'Energy';
end
title({sprintf('Condition %d',con), str, sprintf('%i voxels',length(j))})
% contrast
%--------------------------------------------------------------------------
subplot(2,1,2)
plot(pst,W)
axis square
xlabel('PST {ms}')
ylabel('contrast')
drawnow