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