[Master Index] [Index for Toolbox]

# manage_corticalscouts

## (Toolbox/manage_corticalscouts.m in BrainStorm 2.0 (Alpha))

### Function Synopsis

    varargout = manage_corticalscouts(action,varargin)

### Help Text

    MANAGE_CORTICALSCOUTS - Application M-file for manage_corticalscouts.fig
     function varargout = manage_corticalscouts(action,varargin)

### Cross-Reference Information

This function calls

    brainstorm_filt                    C:\BrainStorm_2001\Toolbox\brainstorm_filt.m
    bst_color_scheme                   C:\BrainStorm_2001\Toolbox\bst_color_scheme.m
    bst_layout                         C:\BrainStorm_2001\Toolbox\bst_layout.m
    bst_message_window                 C:\BrainStorm_2001\Toolbox\bst_message_window.m
    bst_wavedata_display               C:\BrainStorm_2001\Toolbox\bst_wavedata_display.m
    curvature_cortex                   C:\BrainStorm_2001\Toolbox\curvature_cortex.m
    dataplot_cb                        C:\BrainStorm_2001\Toolbox\dataplot_cb.m
    findclosest                        C:\BrainStorm_2001\Toolbox\findclosest.m
    inorcol                            C:\BrainStorm_2001\Toolbox\inorcol.m
    mutincomp                          C:\BrainStorm_2001\Toolbox\mutincomp.m
    norcol                             C:\BrainStorm_2001\Toolbox\norcol.m
    norlig                             C:\BrainStorm_2001\Toolbox\norlig.m
    patch_swell                        C:\BrainStorm_2001\Toolbox\patch_swell.m
    smooth_cortex                      C:\BrainStorm_2001\Toolbox\smooth_cortex.m
    togglebuttoncolor                  C:\BrainStorm_2001\Toolbox\togglebuttoncolor.m
    tri_area                           C:\BrainStorm_2001\Toolbox\tri_area.m
    vertices_connectivity              C:\BrainStorm_2001\Toolbox\vertices_connectivity.m
    view_surface                       C:\BrainStorm_2001\Toolbox\view_surface.m

This function is called by

    dataplot_cb                        C:\BrainStorm_2001\Toolbox\dataplot_cb.m

### Listing of function C:\BrainStorm_2001\Toolbox\manage_corticalscouts.m

    function varargout = manage_corticalscouts(action,varargin)
    %MANAGE_CORTICALSCOUTS - Application M-file for manage_corticalscouts.fig
    % function varargout = manage_corticalscouts(action,varargin)

    %<autobegin> ---------------------- 26-May-2004 11:30:55 -----------------------
    % --------- Automatically Generated Comments Block Using AUTO_COMMENTS ---------
    %
    % CATEGORY: Visualization
    %
    % Alphabetical list of external functions (non-Matlab):
    %   toolbox\brainstorm_filt.m
    %   toolbox\bst_color_scheme.m
    %   toolbox\bst_layout.m
    %   toolbox\bst_message_window.m
    %   toolbox\bst_wavedata_display.m
    %   toolbox\curvature_cortex.m
    %   toolbox\dataplot_cb.m
    %   toolbox\findclosest.m
    %   toolbox\inorcol.m
    %   toolbox\mutincomp.m
    %   toolbox\norcol.m
    %   toolbox\norlig.m
    %   toolbox\patch_swell.m
    %   toolbox\smooth_cortex.m
    %   toolbox\togglebuttoncolor.m
    %   toolbox\tri_area.m
    %   toolbox\vertices_connectivity.m
    %   toolbox\view_surface.m
    %
    % Application data and their calls in this file:
    %   'FVCData'
    %   'Scouts'
    %   'TileType'
    %   'TriArea'
    %
    %   setappdata(ParamFig,'TileType','Tile')
    %   setappdata(data.Results.Display.Handles.Figures.TimeSeries,'TileType','T')
    %   setappdata(data.Results.Display.Handles.hPatch,'FVCData',...
    %   setappdata(data.Results.Display.Handles.hPatch,'Scouts',Scouts)
    %   setappdata(data.Results.Display.Handles.hPatch,'Scouts',Scouts);
    %   setappdata(data.Results.Display.Handles.hPatch,'TriArea',TriArea)
    %   setappdata(fActivation,'TileType','T')
    %
    %   FVCData = getappdata(data.Results.Display.Handles.hPatch,'FVCData');
    %   Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');
    %   TriArea = getappdata(data.Results.Display.Handles.hPatch,'TriArea');
    %
    % Figure Files opened by this function:
    %   'manage_corticalscouts.fig'
    %
    %   Format of strings below: Type:Style:Tag, "String", CallBack Type and Call
    %   <automatic> callback is <Tag>_Callback by Matlab default
    %
    % Callbacks by figure manage_corticalscouts.fig
    %   uicontrol:checkbox:AbsoluteCurrent "Absolute values" uses Callback for
    %     manage_corticalscouts mutincomp_meanmax
    %   uicontrol:pushbutton:DeleteCorticalSpot "Delete" uses Callback for
    %     manage_corticalscouts DeleteCorticalSpot
    %   uicontrol:pushbutton:Hpushbutton35 "Activate" uses Callback for
    %     manage_corticalscouts CorticalSpotActivity
    %   uicontrol:pushbutton:LoadCorticalSpot "Load" uses Callback for
    %     manage_corticalscouts LoadCorticalSpot
    %   uicontrol:pushbutton:pushbutton38 "+" uses Callback for manage_corticalscouts GrowCorticalArea
    %   uicontrol:pushbutton:pushbutton39 "-" uses Callback for manage_corticalscouts ReduceCorticalArea
    %   uicontrol:pushbutton:pushbutton41 "MRI" uses Callback for
    %     manage_corticalscouts ImportScoutsFromMRI
    %   uicontrol:pushbutton:pushbutton42 "Threshold" uses Callback for
    %      manage_corticalscouts CorticalScoutFromThres
    %   uicontrol:pushbutton:pushbutton43 "Corr. with sensor" uses Callback for
    %     manage_corticalscouts CorrelationMapFromSensor
    %   uicontrol:pushbutton:Qpushbutton7 "Close" uses Callback for close(gcbf)
    %   uicontrol:pushbutton:RenameCorticalSpot "Rename" uses Callback for
    %     manage_corticalscouts RenameCorticalSpot
    %   uicontrol:pushbutton:SaveCorticalSpot "Save" uses Callback for
    %     manage_corticalscouts SaveCorticalSpot
    %   uicontrol:pushbutton:SelectCorticalSpot "Probe" uses Callback for
    %     manage_corticalscouts SelectCorticalSpot
    %   uicontrol:radiobutton:AllCorticalArea "All" uses Callback for
    %     manage_corticalscouts mutincomp_meanmax
    %   uicontrol:radiobutton:MaxCorticalArea "Max" uses Callback for
    %     manage_corticalscouts mutincomp_meanmax
    %   uicontrol:radiobutton:MeanCorticalArea "Mean" uses Callback for
    %     manage_corticalscouts mutincomp_meanmax
    %   uicontrol:togglebutton:pushbutton40 "Show selected" uses Callback for
    %     manage_corticalscouts ShowClusters
    %
    % At Check-in: $Author: Mosher $  $Revision: 20 $  $Date: 5/26/04 9:59a $
    %
    % This software is part of BrainStorm Toolbox Version 2.0 (Alpha) 24-May-2004
    %
    % Principal Investigators and Developers:
    % ** Richard M. Leahy, PhD, Signal & Image Processing Institute,
    %    University of Southern California, Los Angeles, CA
    % ** John C. Mosher, PhD, Biophysics Group,
    %    Los Alamos National Laboratory, Los Alamos, NM
    % ** Sylvain Baillet, PhD, Cognitive Neuroscience & Brain Imaging Laboratory,
    %    CNRS, Hopital de la Salpetriere, Paris, France
    %
    % See BrainStorm website at http://neuroimage.usc.edu for further information.
    %
    % Copyright (c) 2004 BrainStorm by the University of Southern California
    % This software distributed  under the terms of the GNU General Public License
    % as published by the Free Software Foundation. Further details on the GPL
    % license can be found at http://www.gnu.org/copyleft/gpl.html .
    %
    % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE
    % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY
    % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF
    % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY
    % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE.
    %<autoend> ------------------------ 26-May-2004 11:30:55 -----------------------

    % /---Script Author--------------------------------------\
    % |                                                      |
    % | *** Sylvain Baillet, Ph.D.                           |
    % | Cognitive Neuroscience & Brain Imaging Laboratory    |
    % | CNRS UPR640 - LENA                                   |
    % | Hopital de la Salpetriere, Paris, France             |
    % | sylvain.baillet@chups.jussieu.fr                     |
    % |                                                      |
    % \------------------------------------------------------/

    DefaultScoutColor = [0 .3 0]; % Default color for selected cortical scout area
    DefaultLabelColor = [1 1 1]; % default text color for scout labels

    global data % Get informations from the main Viewer window

    switch(action)

    case 'create' % Create display-parameter window

        ParamFig = openfig('manage_corticalscouts.fig','reuse');
        setappdata(ParamFig,'TileType','Tile')
        bst_color_scheme(ParamFig);
        bst_layout('align',ParamFig,2,2,4);
        set(ParamFig,'Visible','on')

        % Get previous scouts in memory
        if isappdata(data.Results.Display.Handles.hPatch,'Scouts')
            Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');
            nScouts = length(Scouts);
            hScoutsManagerFig = guihandles(ParamFig);
            set(hScoutsManagerFig.CorticalSpotList,'String',{Scouts(:).Label},...
                'Max',nScouts,'Value',1)
        end

        %----------------------------------------------------------------------------

    case 'SelectCorticalSpot'

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end

        figure(data.Results.Display.Handles.Figures.Surfaces)
        hold on

        if nargin == 1
            ginput(1);
        else
            data.Results.Display.Handles.hPatch = (varargin{2});
            figure(data.Results.Display.Handles.Surfaces)
            hold on
        end

        scurrent = plot3(0,0,0,'o','parent',gca,'Markersize',5,'Markerfacecolor','r');
        set(scurrent,'visible','off')

        vertices = get(data.Results.Display.Handles.hPatch,'vertices');
        % Search for intersection with cortical nodes which
        % are considered as visible only, ie FVCData ~- NaN
        vert_isnan = get(data.Results.Display.Handles.hPatch,'FaceVertexCdata');
        if size(vert_isnan,2) == 1
            vert_isnan = find(~isnan(vert_isnan));
        else
            vert_isnan = sum(vert_isnan ,2);
            vert_isnan = find(~isnan(vert_isnan));
        end

        vertices = vertices(vert_isnan,:);

        x = vertices(:,1)';
        y = vertices(:,2)';
        z = vertices(:,3)';
        clear vertices

        if nargin == 1 % Vertex selection from a manual probe

            % Get surface vertex which distance to ray entering the viewing box is minimum

            C = get(gca,'Currentpoint');

            % Unit vector on traced ray accross viewing box from entering point
            u = (C(1,:)-C(2,:))'/norm(C(1,:)-C(2,:));

            inorm=  1:length(x);
            tempo1 = [C(1,1)-x(inorm);C(1,2)-y(inorm);C(1,3)-z(inorm)];
            DIR = u * ones(1,length(inorm));
            tempo = cross(tempo1,DIR);
            clear DIR
            % Compute distance of all vertices to ray
            distdroite = norcol(tempo);
            distboite = norcol(tempo1);
            distdroite = distdroite/max(distdroite);
            distboite = distboite/max(distboite);
            [minn,im] = min(.04*distboite+0.96*distdroite);
            clear tempo tempo1

        else % Point location is passed as an argument
            inorm=  1:length(x);
            im = varargin{1};
        end

        set(scurrent,'Xdata',x(inorm(im)),'Ydata',y(inorm(im)),'Zdata',z(inorm(im)))
        drawnow

        set(scurrent,'visible','on')
        if isempty(im)
            warndlg('Please reselect your location','Location error')
        end

        % Store cortical scout information as appdata of corresponding patch object
        Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');
        iScout = length(Scouts) + 1;

        Scouts(iScout).Vertex = vert_isnan(inorm(im)); % Vertex index for current scout
        Scouts(iScout).Handle = scurrent; % Handle to plot of scout location

        htext = text(1.05*x(inorm(im)),1.05*y(inorm(im)),1.05*z(inorm(im)),int2str(length(Scouts)));
        set(htext,'FontWeight','normal','color','g','Fontname','helvetica','Fontsize',10,'FontUnits','Point')
        Scouts(iScout).HandleLabels = htext; % Handle of text object for scout label
        Scouts(iScout).Label = get(htext,'String');

        setappdata(data.Results.Display.Handles.hPatch,'Scouts',Scouts);

        nScouts = length(Scouts);

        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);
        set(hScoutsManagerFig.CorticalSpotList,'String',{Scouts(:).Label},...
            'Max',nScouts,'Value',1)

        rotate3d on

        %----------------------------------------------------------------------------
    case 'DeleteCorticalSpot'

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end

        %figure(data.Results.Display.Handles.Figures.Surfaces)
        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);
        SelectedScout = get(hScoutsManagerFig.CorticalSpotList,'Value');

        % Update label information
        Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');
        RemainingScouts = setdiff([1:length(Scouts)],SelectedScout);

        % Delete graphical objects
        if ~isempty(Scouts)
            delete(Scouts(SelectedScout).Handle)
            delete(Scouts(SelectedScout).HandleLabels)
            Scouts =  Scouts(RemainingScouts);
            set(hScoutsManagerFig.CorticalSpotList,'String',{Scouts(RemainingScouts).Label},'Value',1,'Max',length(Scouts));
        else
            set(hScoutsManagerFig.CorticalSpotList,'String',{''},'Value',1,'Max',1);
        end
        setappdata(data.Results.Display.Handles.hPatch,'Scouts',Scouts);

        %----------------------------------------------------------------------------
    case 'RenameCorticalSpot'

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end

        figure(data.Results.Display.Handles.Figures.Surfaces)
        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        SelectedScout = get(hScoutsManagerFig.CorticalSpotList,'Value');
        SelectedScout = SelectedScout(1); % only one at a time please

        Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');

        Title = '';
        Prompt = sprintf('Please enter a new label for %s',Scouts(SelectedScout).Label);
        tmp = inputdlg(Prompt,Title);
        if isempty(tmp), return, end
        Scouts(SelectedScout).Label = tmp{:};
        set(hScoutsManagerFig.CorticalSpotList,'String',{Scouts(:).Label})

        figure(data.Results.Display.Handles.Figures.Surfaces)
        findobj(0,'tag','tessellation_window');
        set(Scouts(SelectedScout).HandleLabels,'String',Scouts(SelectedScout).Label)
        setappdata(data.Results.Display.Handles.hPatch,'Scouts',Scouts);

        %----------------------------------------------------------------------------

    case {'GrowCorticalArea','ReduceCorticalArea'} % Grow/shrink selected scout area
        % by including connected successive rings of connected vertices

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end
        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        if ~isfield(data.Results.Display.OPTIONS,'VertConn') % Vertex connectivity not available here - load or compute

            % Is vertex connectivity available ?
            load(fullfile(Users.SUBJECTS,Users.CurrentData.SubjectFile),'VertConn');
            if ~exist('VertConn','var') % Vertex connectivity not computed yet
                VertConn = '';
            end

            VertConnFile = VertConn; % Filename containing connectivity information
            [pathname, filename] = fileparts(fullfile(Users.SUBJECTS,data.Results.OPTIONS.GridLoc));

            cd(pathname)
            if ~exist(VertConnFile,'file')

                % How many surfaces in tessellation file ?
                % should be only one but older BrainStorm files may contain several
                load(fullfile(Users.SUBJECTS,data.Results.OPTIONS.GridLoc),'Comment');
                nsurfaces = length(Comment); % Number of surfaces in tessellation file
                VertConn = cell(nsurfaces,1); % Create cell array where to store vertex connectivity values

                VertConn{data.Results.OPTIONS.iGrid(1)} = vertices_connectivity(fv); % compute vertex connectivity
                [pathname, filename] = fileparts(fullfile(Users.SUBJECTS,data.Results.OPTIONS.GridLoc));
                cd(pathname)
                if ~exist(VertConnFile,'file')
                    VertConnFile = [filename,'_vertconn.mat']; % Where to save it
                end

                % Save
                save(fullfile(pathname,VertConnFile),'VertConn');
                % Update tessellation file information
                tmp = VertConn; % CBB VertConn should be stored tessellation file not in separate file (SB, 09-Oct-2003)
                VertConn = VertConnFile;
                save(fullfile(Users.SUBJECTS,Users.CurrentData.SubjectFile),'VertConn','-append');
                data.Results.Display.OPTIONS.VertConn = tmp; clear tmp nsurfaces

            else % load existing vertex connectivity map

                load(fullfile(pathname,VertConnFile))
                data.Results.Display.OPTIONS.VertConn = VertConn; clear VertConn

            end

        end

        % Now grow a patch around the selected probe by adding a ring neighbors

        SelectedScout = get(hScoutsManagerFig.CorticalSpotList,'Value');
        Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');

        switch(action)
        case 'GrowCorticalArea'
            Scouts(SelectedScout).Vertex = [Scouts(SelectedScout).Vertex,...
                    patch_swell([Scouts(SelectedScout).Vertex],data.Results.Display.OPTIONS.VertConn)];
        case 'ReduceCorticalArea'
            % Reduce more gradually the area of the cortical patch to be monitored
            if length(Scouts(SelectedScout).Vertex)>1
                Scouts(SelectedScout).Vertex = [Scouts(SelectedScout).Vertex(1:end-1)];
            end
        end

        % Now show clusters
        % Keep track of the original activation vertex colordata
        if ~isappdata(data.Results.Display.Handles.hPatch,'FVCData')
            setappdata(data.Results.Display.Handles.hPatch,'FVCData',...
                get(data.Results.Display.Handles.hPatch,'FaceVertexCData'));
        end
        FVCData = getappdata(data.Results.Display.Handles.hPatch,'FVCData');

        % RGB Values
        Scouts(SelectedScout).Color = DefaultScoutColor; % CBB | User may assign/alter scout patch color ?
        FVCData(Scouts(SelectedScout).Vertex,:) = repmat(Scouts(SelectedScout).Color,length(Scouts(SelectedScout).Vertex),1);

        set(data.Results.Display.Handles.hPatch,'FaceVertexCData',FVCData);

        % Compute corresponding surface area
        if ~isappdata(data.Results.Display.Handles.hPatch,'TriArea')
            TriArea = 1e4*tri_area(get(data.Results.Display.Handles.hPatch,'Faces'), get(data.Results.Display.Handles.hPatch,'Vertices'));
            setappdata(data.Results.Display.Handles.hPatch,'TriArea',TriArea)
        else
            TriArea = getappdata(data.Results.Display.Handles.hPatch,'TriArea');
        end

        % CBB make the following area computation faster...
        kk = 0;
        for k = Scouts(SelectedScout).Vertex
            kk = kk+1;
            [i,j] = find(get(data.Results.Display.Handles.hPatch,'Faces')-k == 0);
            tri{kk}= i';
        end
        if isempty(tri{1})
            tria = [];
        else
            tria = unique([tri{:}]);
        end
        o_area = sum(TriArea(tria))/3; %in cm2

        set(hScoutsManagerFig.ScoutArea,'String',sprintf('%3.1f cm2',o_area))

        setappdata(data.Results.Display.Handles.hPatch,'Scouts',Scouts)

        %----------------------------------------------------------------------------

    case 'ShowClusters' % Show all cortical scouts/clusters at once

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end
        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);
        togglebuttoncolor(gcbo)

        Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');

        % Which clusters were selected ?
        SelectedScout = get(hScoutsManagerFig.CorticalSpotList,'Value');

        % Original current mapping
        FVCData = getappdata(data.Results.Display.Handles.hPatch,'FVCData');

        if get(gcbo,'Value') % Show selected clusters
            FVCData([Scouts(SelectedScout).Vertex],:) = repmat(DefaultScoutColor,length([Scouts(SelectedScout).Vertex]),1);
        end

        set(data.Results.Display.Handles.hPatch,'FaceVertexCData',FVCData);

        %----------------------------------------------------------------------------

    case 'SaveCorticalSpot' % Save cortical scout locations
        % Cortical scouts need to be indexed with both the corresponding cortical surface name
        % and the current data set name

        data.Results.Display.Handles.hPatch  = findobj(0,'tag','tessellation_window');
        CorticalScouts = get(data.Results.Display.Handles.hPatch,'Userdata');

        CorticalScouts.HandleLabels = get(CorticalScouts.HandleLabels,'String');
        CorticalScouts.Handle = [get(CorticalScouts.Handle,'Xdata');...
                get(CorticalScouts.Handle,'Ydata');...
                get(CorticalScouts.Handle,'Zdata')];
        if iscell( CorticalScouts.Handle)
            CorticalScouts.Handle = [CorticalScouts.Handle{:}];
        end

        CorticalScouts.Handle = reshape(CorticalScouts.Handle,length(CorticalScouts.HandleLabels),3);
        % CorticalScouts.Handle is now Number of Scouts x 3

        ScoutsManagerFig = findobj(0,'Tag','tesselation_select');
        hSelect = guihandles(ScoutsManagerFig);

        % What's the name of the current cortical envelope ?
        ActiveTess = get(hSelect.removed,'String'); % Find the active Cortical surface
        iCortex = get(hSelect.removed,'Value');
        if iscell(ActiveTess)
            ActiveTess= ActiveTess{iCortex};
        end

        if isfield(CorticalScouts,'CorticalProbePatches') % Process members of cortical patches to get their x,y,z's
            Visu = get(DATAPLOT,'Userdata');
            try
                load(Visu.Tesselation,'Comment','Vertices')
            catch
                cd(Users.SUBJECTS)
                load(Visu.Tesselation,'Comment','Vertices')
            end
            % What's the current surface ?
            imesh = find(strcmp(Comment,ActiveTess));
            Vertices = Vertices{imesh};
            CorticalScouts.CorticalProbePatchesXYZ = cell(size(CorticalScouts.CorticalProbePatches));
            for k=1:length(CorticalScouts.CorticalProbePatches)   % for each area
                CorticalScouts.CorticalProbePatchesXYZ{k} = ...
                    Vertices(:,CorticalScouts.CorticalProbePatches{k});
            end

        end

        % What's the name of the current data set ?
        ResultFiles = get(hSelect.ResultFiles,'String');
        ResultFile = ResultFiles{get(hSelect.ResultFiles,'Value')};

        cd(Users.STUDIES)
        dirr = fileparts(Users.CurrentData.StudyFile);
        cd(dirr);

        [filename, pathname] = uiputfile('CorticalScout.mat', 'Save Cortical Scout in...');
        save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat');

        %----------------------------------------------------------------------------

    case 'LoadCorticalSpot' % Load cortical scout locations
        data.Results.Display.Handles.hPatch  = findobj(0,'tag','tessellation_window');

        if nargin == 1

            CorticalScouts = get(data.Results.Display.Handles.hPatch,'Userdata');
            if ~isempty(CorticalScouts) % some exist - remove
                if isfield(CorticalScouts,'CorticalMarkers')
                    delete(CorticalScouts.Handle)
                    delete(CorticalScouts.HandleLabels)
                    clear CorticalScouts
                end
            end

            cd(Users.STUDIES)
            dirr = fileparts(Users.CurrentData.StudyFile);
            cd(dirr);

            [filename, pathname] = uigetfile('CorticalScout.mat', 'Save Cortical Scout in...');
            if filename == 0
                return
            end
            load(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat');
        else
            load(varargin{1}, 'ResultFile','ActiveTess','CorticalScouts','-mat');
        end

        figure(data.Results.Display.Handles.hPatch), hold on
        MainAxes = findobj(data.Results.Display.Handles.hPatch,'Tag','MainAxes');
        vertices = get(findobj(MainAxes,'type','patch'),'vertices');
        x = vertices(:,1)';
        y = vertices(:,2)';
        z = vertices(:,3)';
        clear vertices

        CorticalScouts.Handle = zeros(length(CorticalScouts.Vertex),1);
        for k = 1:length(CorticalScouts.Vertex)
            scurrent = plot3(0,0,0,'o','parent',MainAxes,'Markersize',5,'Markerfacecolor','r');
            set(scurrent,'visible','off')
            set(scurrent,'Xdata',x(CorticalScouts.Vertex(k)),...
                'Ydata',y(CorticalScouts.Vertex(k)),...
                'Zdata', z(CorticalScouts.Vertex(k)))
            set(scurrent,'visible','on')
            CorticalScouts.Handle(k) = scurrent;

            r_text =1.1;

            if iscell(CorticalScouts.HandleLabels)
                htext = text(r_text*x(CorticalScouts.Vertex(k)),...
                    r_text*y(CorticalScouts.Vertex(k)),...
                    r_text*z(CorticalScouts.Vertex(k)),...
                    CorticalScouts.HandleLabels{k});
            else
                htext = text(r_text*x(CorticalScouts.Vertex(k)),...
                    r_text*y(CorticalScouts.Vertex(k)),...
                    r_text*z(CorticalScouts.Vertex(k)),...
                    CorticalScouts.HandleLabels);

            end

            set(htext,'FontWeight','normal','color','g','Fontname','helvetica',...
                'Fontsize',10,'FontUnits','Point')

            Label_tmp(k) = htext;
        end

        ScoutsManagerFig = findobj(0,'Tag','tesselation_select');
        hScoutsManagerFig = guihandles(ScoutsManagerFig);
        set(hScoutsManagerFig.CorticalSpotList,'String',CorticalScouts.HandleLabels,...
            'Value',1,'Max', length(CorticalScouts.HandleLabels))

        CorticalScouts.HandleLabels = Label_tmp; clear Label_tmp;

        set(data.Results.Display.Handles.hPatch,'Userdata',CorticalScouts);

        figure(data.Results.Display.Handles.hPatch)
        rotate3d on

        %----------------------------------------------------------------------------

    case 'mutincomp_meanmax' % Mutually icompatible checkboxes
        handles = guihandles(gcbf);

        mutincomp([handles.MeanCorticalArea,handles.MaxCorticalArea,handles.AllCorticalArea])
        h = findobj([handles.MeanCorticalArea,handles.MaxCorticalArea,handles.AllCorticalArea],'Value',1);
        if length(h)>1
            set(h(2:end),'Value',0)
        end

        %----------------------------------------------------------------------------

    case 'CorticalSpotActivity'

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end
        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        % Get scout information
        SelectedScout = get(hScoutsManagerFig.CorticalSpotList,'Value'); % Which scout was selected ?
        Scouts = getappdata(data.Results.Display.Handles.hPatch,'Scouts');

        % What kind of display is wanted here ?
        MEAN = get(hScoutsManagerFig.MeanCorticalArea,'Value');
        MAX = get(hScoutsManagerFig.MaxCorticalArea,'Value');
        ALL = get(hScoutsManagerFig.AllCorticalArea,'Value');

        % -> Prepare cell array containing time series to display
        for k = 1:length(SelectedScout) % For each cortical survey area
            if MEAN == 1% Average of the patch activity at each time instant
                if get(hScoutsManagerFig.AbsoluteCurrent,'Value')
                    CorticalActivity{k} = mean(abs(double(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:))),1);
                else
                    CorticalActivity{k} = sign(mean(double(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:))))...
                        .* mean(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:),1) ;
                end
            elseif MAX==1 % Strongest
                if get(hScoutsManagerFig.AbsoluteCurrent,'Value')
                    CorticalActivity{k} = max(abs(double(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:))),[],1);
                else
                    CorticalActivity{k} = max(double(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:)),[],1);
                end

            else % Display every source activity in the patch
                % All sources need to be displayed
                if get(hScoutsManagerFig.AbsoluteCurrent,'Value')
                    CorticalActivity{k} = abs(double(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:)));
                else
                    CorticalActivity{k} = double(data.Results.ImageGridAmp(Scouts(SelectedScout(k)).Vertex,:));
                end
                % Detect Maxima in amplitudes (needed for proper display in the offset plot)
                maxCorticalActivity{k} = sign(min(CorticalActivity{k})).*max(abs(CorticalActivity{k}));
            end
        end
        % <- Prepare cell array containing time series to display

        % Now display these time series
        if ~isfield(data.Results.Display.Handles.Figures,'TimeSeries')
            fActivation = figure;
            data.Results.Display.Handles.Figures.TimeSeries = fActivation;
            setappdata(fActivation,'TileType','T')
            bst_color_scheme(fActivation)
            bst_layout('align',fActivation,2, 2, 3)
            bst_layout('align',data.Results.Display.Handles.Figures.Surfaces,2, 2, 1)
        else
            figure(data.Results.Display.Handles.Figures.TimeSeries)
            clf
            setappdata(data.Results.Display.Handles.Figures.TimeSeries,'TileType','T')
            bst_color_scheme(data.Results.Display.Handles.Figures.TimeSeries)
            bst_layout('align',data.Results.Display.Handles.Figures.TimeSeries,2, 2, 3)
            bst_layout('align',data.Results.Display.Handles.Figures.Surfaces,2, 2, 1)

        end

        % Display set-up
        tail = {'MEAN','MAX','ALL'};
        set(gcf,'Tag','source_time_series','Name',['Activation time series: ', tail{find([MEAN,MAX,ALL])}])
        Color = get(gca,'ColorOrder'); % Default Colormapping for line plots

        ColumnLayout = 1; % Flag
        OPTIONS.nColumnLayout = 1; % Number of columns
        OverlayAllChannels = 0;
        nDispTypes = 1;
        nSets = length(SelectedScout);
        OPTIONS.Time = linspace(data.Display.Time(1),data.Display.Time(end),data.Display.NumberOfSamples);
        OPTIONS.CurrentTime = dataplot_cb('GET','current_time');

        % Initialize column plot structure
        tmp = deal(struct('lines',{cell(1,nSets)},'axes',zeros(OPTIONS.nColumnLayout,1),'ytick',[]));
        PlotHandles.PlotColumn = tmp;
        clear tmp

        % Display parameter for proper layout of time series
        OPTIONS.Fmax = [];
        for iSet = 1:nSets
            OPTIONS.Fmax(iSet) = max(max(abs(CorticalActivity{iSet})));
        end

        OPTIONS.WaveLabel = {Scouts.Label};
        OPTIONS.DataType = 'source';
        OPTIONS.Modality = 1;

        OPTIONS.LineColor = num2cell(rand(length(CorticalActivity),3),2);

        switch(get(hScoutsManagerFig.popupScoutPlotType,'Value'))
        case 1 % Overlay all timeseries
        case 2 % Column plot
            OPTIONS.DisplayTypes = [1 0 0];
            if 1,%size(cat(1,CorticalActivity{:}),1)/length(CorticalActivity) > 1 % Several sources per scouts
                OPTIONS.Modality = 1:length(CorticalActivity);
                OPTIONS.SelectedChannels{1} = 1:size(CorticalActivity{1},1);
                for k = 2:length(CorticalActivity)
                    OPTIONS.SelectedChannels{k} = size(CorticalActivity{k-1},1)+1:size(CorticalActivity{k-1},1)+size(CorticalActivity{k},1);
                end
            end
            CorticalActivity = {cat(1,CorticalActivity{:})};
        end
        OPTIONS.DisplayTypes = [1 0 0];
        [data.Results.Display.Scouts.Handles,OPTIONS] = ...
            bst_wavedata_display(CorticalActivity,OPTIONS);

    %----------------------------------------------------------------------------

    case 'ImportScoutsFromMRI' % Create a scout file from points selected in the MR

        if ~ishandle(data.Results.Display.Handles.Figures.Surfaces)
            return
        end
        ScoutsManagerFig = gcbf;
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        cd(Users.STUDIES);
        [filename, pathname] = uigetfile('*.txt', 'Select an MRI Point File');
        if filename == 0, return, end
        CorticalScouts = struct('MarkersLabels','','CorticalSpots',[],'CorticalMarkers',[]);

        [Number,Labels,X,Y,Z,Xmri,Ymri,Zmri] = ...
            textread(fullfile(pathname,filename),'%d %s %f %f %f %f %f %f',-1);
        clear Number Xmri Ymri Zmri

        Vertices = get(data.Results.Display.Handles.hPatch,'Vertices');
        X = X/1000;
        Y = Y/1000;
        Z = Z/1000;

        for k = 1:length(X) % Find closest vertex in the tessellation
            [mm Scouts.Vertex(k)] = min(norcol(...
                [Vertices(1,:)-X(k); ...
                    Vertices(2,:)-Y(k); ...
                    Vertices(3,:)- Z(k)]));
            %Scouts.Handle(k,:) = Vertices(:,Scouts.Vertex(k))';
        end
        %Scouts.Handle = Vertices(:,Scouts.Vertex)';
        clear Vertices

        % Create Cortical Scout File
        cd(Users.STUDIES);
        [filename, pathname] = uiputfile(['CorticalScoutFromMRI.mat'], 'Save Cortical Scout in...');
        save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat');

        % Visualization
        dataplot_cb('LoadCorticalSpot',fullfile(pathname,filename))

        %----------------------------------------------------------------------------

    case 'CorrelationWithDepthElectrodes' % Compute time-series correlation between recorded signals from
        % depth electrodes and corresponding locations in imaging map

        data.Results.Display.Handles.hPatch  = findobj(0,'tag','tessellation_window');
        %CorticalScouts = get(data.Results.Display.Handles.hPatch,'Userdata');
        ScoutsManagerFig = findobj(0,'Tag','tesselation_select');
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        % Load specific cortical scout file (depth electrodes)
        %DepthScouts = load('I:\Data\Studies\Epilepsie\02May02\DepthElectrodes_Scouts.mat');
        DepthScouts = load('C:\Users\Silvin_E\BrainStorm2001\Studies\Epilepsie\02May02\DepthElectrodes_Scouts.mat');
        Visu = get(DATAPLOT,'Userdata');
        % Identification of the active mesh surfaces
        try
            load(Visu.Tesselation,'Comment')
        catch
            cd(Users.SUBJECTS)
            load(Visu.Tesselation,'Comment')
        end
        available = findobj(ScoutsManagerFig,'Tag','available');
        removed =  findobj(ScoutsManagerFig,'Tag','removed');
        availableID = get(removed,'Value');
        IDs = get(removed,'String');
        if isempty(IDs), return, end

        if ~iscell(IDs)
            imesh = find(strcmp(IDs,Comment));
        end

        nsurf = imesh(availableID); % Selected surface
        load(Visu.Tesselation,'Faces','Vertices')
        Faces = Faces{nsurf};
        Vertices = Vertices{nsurf};
        % Compute tri area
        A = tri_area(Faces,100*Vertices');

        % First ask
        %  on which time window to compute correlation
        Results = get(hScoutsManagerFig.ResultFiles,'Userdata');
        Prompt = {...
                'Time window for correlation computation (in ms):',...
            };

        Answer = inputdlg(Prompt,'',1,{sprintf('%3.2f %3.2f',Results.ImageGridTime(1)*1000, Results.ImageGridTime(end)*1000')});
        if isempty(Answer{1})
            return
        end

        CorrTimeWin = str2num(Answer{1})/1000; % Time window for correlation computation
        clear Answer

        % Now for each depth electrode - compute correlation between recorded signal and estimated source time courses
        for k = 1:length(DepthScouts.CorticalScouts.Vertex)
            % Find sensor in the data's Channel structure
            DepthScouts.CorticalScouts.HandleLabels{k}

            CorrRefChan = find(strcmpi(DepthScouts.CorticalScouts.HandleLabels{k},{Visu.Channel.Name}));
            if isempty(CorrRefChan), return, end % Channel name not found
            CorrRefChanName = Visu.Channel(CorrRefChan).Name;
            F = Visu.Data.F(CorrRefChan,:);
            % Find time indices for correlation computation
            % Trim out source and sensor time series
            Results = get(hScoutsManagerFig.ResultFiles,'Userdata');
            F = F(Results.Time);
            TimeInd = findclosest(CorrTimeWin,Results.ImageGridTime');

            load(fullfile(Users.SUBJECTS,Users.CurrentData.SubjectFile),'VertConn'); % Is the vertex connectivity available ?
            load(fullfile(Users.SUBJECTS,fileparts(Users.CurrentData.SubjectFile),VertConn))
            % Now grow a patch around the selected probe and selected neighbors
            patchh = ...
                [DepthScouts.CorticalScouts.Vertex(k),patch_swell(DepthScouts.CorticalScouts.Vertex(k),VertConn{nsurf})];
            patchh = [patchh,patch_swell(patchh,VertConn{nsurf})];
            %patchh = [patchh,patch_swell(patchh,VertConn{nsurf})];
            %patchh = [patchh,patch_swell(patchh,VertConn{nsurf})];
            kkk = 0;
            for kk=patchh % For each element of the patch
                kkk = kkk+1;
                [i,j] = find(Faces-kk == 0); % Find all triangles for which current parch element is a vertex
                if ~isempty(i)
                    %tri{kkk} = i';
                    VertArea(kkk)= sum(A(i))/3; % Each vertex contributes to 1/3 of the each triangle surface it belongs to
                else
                    kkk = kkk-1;
                end
            end

            %tri = unique([tri{:}]); %
            %area(k) = sum(A(tri))/3;% in cm2

            area(k) = sum(VertArea); % Total area covered by path k

            clear tri kk kkk VertArea
            % take average activity within patch
            %         [maxx ind] = max(abs(Results.ImageGridAmp(patch,TimeInd(1):TimeInd(end))));
            %         Time = TimeInd(1):TimeInd(end);
            %         for time = 1:length(Time)
            %             tmp(time) = maxx(time).*sign(Results.ImageGridAmp(patch(ind(time)),Time(time)));
            %         end
            %         Results.ImageGridAmp = tmp;

            %Results.ImageGridAmp = mean((Results.ImageGridAmp(patch,TimeInd(1):TimeInd(end))));
            %Results.ImageGridAmp = Results.ImageGridAmp - mean(Results.ImageGridAmp);

            [Results.ImageGridAmp,filtwts] = brainstorm_filt(Results.ImageGridAmp(patchh,:),1250,0,70);
            [F,filtwts] = brainstorm_filt(F,1250,0,70);
            Results.ImageGridAmp = Results.ImageGridAmp(:,TimeInd(1):TimeInd(end));
            Results.ImageGridAmp = Results.ImageGridAmp - repmat(mean(Results.ImageGridAmp,2),1,length(TimeInd(1):TimeInd(end)));

            F = F(TimeInd(1):TimeInd(end));
            F = (F - mean(F));
            Results.ImageGridAmp = (double(Results.ImageGridAmp));

            %Compute correlation coefficients for all sources

            [CorrCoeff(k) imax] = max(abs((F/norm(F))...
                *Results.ImageGridAmp'*inorcol(Results.ImageGridAmp')));

            SignCorr(k) = sign(((F/norm(F))...
                *Results.ImageGridAmp(imax,:)'*inorcol(Results.ImageGridAmp(imax,:)')));

            Source(k,:) = Results.ImageGridAmp(imax,:);
            Data(k,:) = F;

            %end

            % Plot
            %for k = 1:length(DepthScouts.CorticalScouts.Vertex)
            if abs(CorrCoeff(k)) > .4
                hfig = figure;
                TimeVec = 1000*linspace(CorrTimeWin(1),CorrTimeWin(2), length(F));
                ploot = 100*Data(k,:)/(norm(Data,'fro')/sqrt(length(DepthScouts.CorticalScouts.Vertex))); % Normalize amplitudes by average signal energy over all electrodes
                plot(TimeVec,ploot,'r','linewidth',2), hold on
                if SignCorr(k) < 0
                    plot(TimeVec,-Source(k,:)*max(abs(ploot))/max(abs(Source(k,:))),'b','linewidth',2);
                else
                    plot(TimeVec, Source(k,:)*max(abs(ploot))/max(abs(Source(k,:))),'b','linewidth',2);
                end
                set(gcf,'color','k')
                set(gca,'xcolor','w','ycolor','w')
                ylabel('% average total signal energy')
                title(sprintf('Channel: %s - Correlation: %3.2f %% - Area Explored: %3.2f cm2',DepthScouts.CorticalScouts.HandleLabels{k},100*abs(CorrCoeff(k)),area(k)),'color','w')
                set(hfig,'Name',CorrRefChanName)
            end
            %end
            ans = input('Plot cortical maps (y/n) ? ','s');
            switch(ans)
            case 'y'

                imax = patchh(imax);
                patchh = ...
                    [DepthScouts.CorticalScouts.Vertex(9),patch_swell(DepthScouts.CorticalScouts.Vertex(9),VertConn{nsurf})];
                patchh = [patchh,patch_swell(patchh,VertConn{nsurf})];
                for kkkk =1 : 35
                    patchh = [patchh,patch_swell(patchh,VertConn{nsurf})];
                end
                Results = get(hScoutsManagerFig.ResultFiles,'Userdata');
                tmp = Results.ImageGridAmp(patchh,TimeInd(1):TimeInd(end));
                Results.ImageGridAmp = NaN * Results.ImageGridAmp(:,TimeInd(1):TimeInd(end));
                Results.ImageGridAmp(patchh,:) = tmp; clear tmp

                % Surface smoothing
                fv.vertices = Vertices';
                fv.faces = Faces;
                load C:\Users\Silvin_E\BrainStorm2001\Subjects\epilepsie\02May02\02May02_tess_vertconn
                VertConn = VertConn{6};
                [smoothedFV,A]=smooth_cortex(fv,VertConn,.3,100);

                %tmpVertices = NaN * Vertices;
                %tmpVertices(:,patchh) = Vertices(:,patchh);
                tmpVertices = NaN * smoothedFV.vertices';
                tmpVertices(:,patchh) = smoothedFV.vertices(patchh,:)';
                [curvature_sigmoid,curvature] = curvature_cortex(fv,VertConn,.1,0);
                curvature(curvature>=0) = .8;
                curvature(curvature<0) = -.8;

                data.curDensityMapArray{1} = [zeros(17,2) (0.5:0.03:1)'
                    zeros(29,1) (0.03:0.034:1)' ones(29,1)
                    (0.3:0.3:1)' ones(3,2)
                    1 1 1
                    ones(26,1) (1:-0.039:0)' (1:-0.039:0)'
                    (1:-0.021:0.5)' zeros(24,2)];

                data.curDensityMapArray{2} = [zeros(17,2) (0.5:0.03:1)' %17
                    zeros(29,1) (0.03:0.034:1)' ones(29,1) %29
                    (0.3:0.3:1)' ones(3,2) %3
                    1 1 1
                    ones(50,2) (1:-0.0202:0)']; %50

                tmp = hot(140);%flipdim(hot(100),1);
                data.curDensityMapArray{3} = tmp(1:100,:);%flipdim(hot(100),1);

                %             [TH,PHI,R] = cart2sph(tmpVertices(1,patchh),tmpVertices(2,patchh),tmpVertices(3,patchh));
                %             PHI2 = zeros(size(PHI));
                %             R2 = R./cos(PHI).^.2;
                %             [tmpVertices(2,patchh),tmpVertices(1,patchh)] = pol2cart(TH,R2);
                %             tmpVertices(3,patchh) = 0;
                %

                [hf,hs,hl] = view_surface('test',Faces,tmpVertices,Results.ImageGridAmp(:,1));
                %             hold on
                subplot(221)
                [hf,hs,hl] = view_surface('test',Faces,tmpVertices,Results.ImageGridAmp(:,1));
                delete(findobj(gcf,'type','light'))
                view(0,0), material dull, camlight,

                hold on
                hax = subplot(222);
                hs(2) = copyobj(hs,hax);
                axis image
                axis off
                view(-180,0), material dull, camlight

                set(hs,'backfacelighting','unlit')
                hold on
                iScout = DepthScouts.CorticalScouts.Vertex(k);
                ind = k;
                hsaxes = get(hs(1),'Parent');
                axes(hsaxes)
                helec = plot3(tmpVertices(1,iScout),tmpVertices(2,iScout),tmpVertices(3,iScout),'ow','MarkerFaceColor','none','MarkerSize',10);
                hbest = plot3(tmpVertices(1,(imax)),tmpVertices(2,(imax)),tmpVertices(3,(imax)),'ow','MarkerFaceColor','none','MarkerSize',5);
                hsaxes = get(hs(2),'Parent');
                axes(hsaxes)
                helec(2) = plot3(tmpVertices(1,iScout),tmpVertices(2,iScout),tmpVertices(3,iScout),'ow','MarkerFaceColor','none','MarkerSize',10);
                hbest(2) = plot3(tmpVertices(1,(imax)),tmpVertices(2,(imax)),tmpVertices(3,(imax)),'ow','MarkerFaceColor','none','MarkerSize',5);
                set(hf,'color','k')
                %colorbar

                subplot(212)
                Time = 1000*Results.ImageGridTime(TimeInd(1):TimeInd(end));
                hp = plot(Time,ploot,'w','linewidth',2);
                %set(hp,'visible','off')

                hold on

                %Source(ind,:) = norcol(F);

                if SignCorr(ind) < 0
                    plot(TimeVec,-Source(ind,:)*max(abs(ploot))/max(abs(Source(ind,:))),'w','linewidth',1);
                else
                    plot(TimeVec, Source(ind,:)*max(abs(ploot))/max(abs(Source(ind,:))),'w','linewidth',1);
                end

                %ploot = Source(ind,:)*max(abs(ploot))/max(abs(Source(ind,:)));
                hcurr = plot(Time(1),ploot(1),'or','linewidth',2);

                set(gca,'xcolor','w','ycolor','w','color','k')
                xlabel('Time (ms)')
                hcurraxes = get(hcurr,'Parent');

                colormap flag; colormenu
                flag = get(gcf,'colormap'); %colormap([0 0 1; repmat([1 0 0],size(flag,1)-1,1)])
                flag = flag(:,[3 2 1]);
                colormap(flag)

                pwd
                %hsaxes = get(hs(1),'Parent');
                %set(hsaxes,'clim',[.98 1])
                %set(hsaxes,'clim',[0 max(abs(Results.ImageGridAmp(:)))])
                %hsaxes = get(hs(2),'Parent');
                %set(hsaxes,'clim',[.98 1])
                %set(hsaxes,'clim',[0 max(abs(Results.ImageGridAmp(:)))])

                % ------------------------------------------------------------------------------
                cd_threshold = .2;
                cd_transparency = 0.2;
                anatomy = 0;
                viewmode = 1; % Real data or 0 = abs values
                colormap_selected = 3;
                movie = 0;
                activations = 0;
                if movie
                    Avifile = uiputfile('*.avi');%TObas4_corr.avi';%[DepthScouts.CorticalScouts.HandleLabels{ind},'_8.avi'];
                    mov = avifile(Avifile,'FPS',2,'QUALITY',100,'compression','indeo5');
                end
                corrsize = 30;%50
                % ------------------------------------------------------------------------------

                if ~activations
                    timee = corrsize/2+1:2:size(Results.ImageGridAmp,2)-corrsize/2;
                else
                    timee = 1:2:size(Results.ImageGridAmp,2);%
                end

                corr = zeros(size(Results.ImageGridAmp(patchh,:),1),length(timee));
                tt = 0;
                hw = waitbar(0,'Computing correlations');
                cc = zeros(length(timee),1);
                for t = timee
                    tt = tt+1;
                    if ~rem(tt,10)
                        waitbar(tt/length(timee))
                    end

                    if ~activations
                        activ = Results.ImageGridAmp(patchh,t-corrsize/2:t+corrsize/2);
                        elec = F(t-corrsize/2:t+corrsize/2);
                        %                     corr(:,tt) = abs(((elec/norm(elec))...
                        %                         *activ'*inorcol(activ')))';
                        %
                        % Compute corrcoef over time and accross cortex (patchh)
                        activ = (activ)/max(abs(activ(:)));
                        energy = norlig(activ);
                        [senergy iener] = sort(energy);
                        activ = activ(iener(end-100+1:end),:)';
                        tmp = corrcoef(activ);
                        cc(tt) = mean(abs(tmp(:)));

                    else
                        if t == timee(1)
                            tmp = Results.ImageGridAmp(patchh,timee);
                            corr = abs(tmp)/max(tmp(:));%abs(activ(:,1+corrsize/2));
                        end
                    end

                end
                close(hw)
                corr(corr<cd_threshold) = 0; %Show current density that is at least 'display_threshold'% the maximum absolute value
                limitValue = max(abs(corr(:)));

                %Apply alpha blending
                %create anatomy and current density colormaps
                if(anatomy==1) anatomy=0.99; end
                scale = linspace(.4,.6,100);%anatomy:(1-anatomy)/99:1;
                data.anatMap = repmat(scale',1,3);
                if(viewmode == 1) %if real values
                    data.curDensityMap = data.curDensityMapArray{colormap_selected};
                else %if abs values
                    data.curDensityMap = data.curDensityMapArray{colormap_selected+2};
                end
                colormap(data.curDensityMap);

                %Get RGB info for anatomy
                min_curv = min(curvature);
                max_curv = max(curvature);
                data.index_anatomy = (floor((curvature-min_curv)*99/(max_curv-min_curv)+1));
                data.anatRGB = data.anatMap(data.index_anatomy,:);

                for t = 1:length(timee)

                    %                 tmp = NaN * Results.ImageGridAmp(:,t);
                    %                 tmp(patchh) = corr(:,t);
                    %
                    if(viewmode == 1)%if real values
                        index_density = floor((corr(:,t)+limitValue)*99/(2*limitValue)+1);
                        data.curDensityMap = data.curDensityMapArray{colormap_selected};
                    else %if abs values
                        corr = abs(corr);
                        index_density = floor((corr(:,t)-limitValue)*99/limitValue+100);
                        data.curDensityMap = data.curDensityMapArray{colormap_selected+2};
                    end
                    data.curDensityRGB = data.curDensityMap(index_density,:);
                    data.toBlend = find(corr(:,t) ~= 0);
                    mixedRGB = data.anatRGB;
                    toBlend = data.toBlend;
                    mixedRGB(patchh(toBlend),:) = cd_transparency*data.anatRGB(toBlend,:)+(1-cd_transparency)*data.curDensityRGB(toBlend,:);

                    set(hs,'FaceVertexCData',mixedRGB);

                    if movie
                        Frame = getframe(gcf); %get(hs,'Parent')
                        mov = addframe(mov,Frame);
                    end
                    set(hcurr,'xdata',Time(timee(t)),'ydata',ploot(timee(t)))
                    drawnow
                    keyboard
                end

                if movie
                    moc = close(mov);
                end

                keyboard

            case 'n'
                if ishandle(hfig)
                    close(hfig)
                end

            end

        end

        bst_message_window({...
                ' ',...
                sprintf('Average Correlation : %3.2f %%',100*mean(abs(CorrCoeff))),...
                sprintf('Average area explored : %3.2f cm2%%',mean(area)),...
                ' '});

        %----------------------------------------------------------------------------
    case 'CorrelationMapFromSensor' % Compute a correlation map between source time series and a the signal from a sensor
        % Useful for instance when looking for areas correlating the most with some depth electrode signal.
        CorrCoefThres = .98;
        data.Results.Display.Handles.hPatch  = findobj(0,'tag','tessellation_window');
        %CorticalScouts = get(data.Results.Display.Handles.hPatch,'Userdata');
        ScoutsManagerFig = findobj(0,'Tag','tesselation_select');
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        % First ask which sensor will work as the reference
        % and on which time window
        Prompt = {...
                'NAME of sensor to act as reference in correlation computation: ',...
                'Time window for correlation computation (in ms):',...
            };

        Answer = inputdlg(Prompt,'',1,{'tobas4',''});

        if isempty(Answer{1})
            return
        end

        CorrRefChan = Answer{1}; % Name of reference channel for correlation computation
        CorrTimeWin = str2num(Answer{2})/1000; % Time window for correlation computation
        clear Answer

        % Find sensor in channels
        Visu = get(DATAPLOT,'Userdata');
        CorrRefChan = find(strcmpi(CorrRefChan,{Visu.Channel.Name}));
        if isempty(CorrRefChan), return, end % Channel name not found
        CorrRefChanName = Visu.Channel(CorrRefChan).Name;
        F = Visu.Data.F(CorrRefChan,:);
        clear Visu
        % Find time indices for correlation computation
        % Trim out source and sensor time series
        Results = get(hScoutsManagerFig.ResultFiles,'Userdata');

        F = F(Results.Time);

        TimeInd = findclosest(CorrTimeWin,Results.ImageGridTime');
        Results.ImageGridAmp = (Results.ImageGridAmp(:,TimeInd(1):TimeInd(end)));
        % Apply amplitude threshold
        M = max(abs(Results.ImageGridAmp),[],2); % Take maximum over time
        MAX = max(M);
        cThres = str2num(get(hScoutsManagerFig.TruncateFactor,'string'))/100;
        % Indices of the sources above threshold
        GoodSrc = find(M >= cThres*MAX);
        Results.ImageGridAmp  = Results.ImageGridAmp(GoodSrc,:);

        Results.ImageGridAmp = Results.ImageGridAmp - repmat(mean(Results.ImageGridAmp,2),1,length(TimeInd(1):TimeInd(end)));
        F = F(TimeInd(1):TimeInd(end));
        F = F - mean(F);
        Results.ImageGridAmp = double(Results.ImageGridAmp);

        %Compute correlation coefficients for all sources
        %     CorrCoeff = abs(F/norm(F))...
        %         *abs(Results.ImageGridAmp'*inorcol(Results.ImageGridAmp'));

        CorrCoeff = abs((F/norm(F))...
            *Results.ImageGridAmp'*inorcol(Results.ImageGridAmp'));

        % Keep only sources which correlate best
        % Indices of the sources above threshold
        ind = find(CorrCoeff >= CorrCoefThres);
        CorticalScouts.Vertex = GoodSrc(ind);
        if isempty(CorticalScouts.Vertex)
            [maxx ind] = max(CorrCoeff);
            CorticalScouts.Vertex = GoodSrc(ind);
        end

        Source = Results.ImageGridAmp(ind,:);

        %     if length( CorticalScouts.Vertex) == 1
        %         figure, plot(F/norm(F),'r'), hold on, plot(Results.ImageGridAmp(ind,:)/norm(Results.ImageGridAmp(ind,:)),'g');
        %     end

        sprintf('Found %d sources correlating at least up to %3.2f with sensor %s', ...
            length(CorticalScouts.Vertex),...
            CorrCoefThres, ...
            CorrRefChanName)

        % Plot
        CorrCoeff = CorrCoeff(ind);
        for k = 1:length(CorticalScouts.Vertex)
            if abs(CorrCoeff(k)) > .4
                hfig = figure;
                TimeVec = 1000*linspace(CorrTimeWin(1),CorrTimeWin(2), length(F));
                ploot = 100*F/(norm(F,'fro')/sqrt(length(CorticalScouts.Vertex))); % Normalize amplitudes by average signal energy over all electrodes
                plot(TimeVec,ploot,'r','linewidth',2), hold on
                plot(TimeVec, Source(k,:)*max(abs(ploot))/max(abs(Source(k,:))),'b','linewidth',2);
                set(gcf,'color','k')
                set(gca,'xcolor','w','ycolor','w')
                ylabel('% average total signal energy')
                title(sprintf('Correlation: %3.2f %%',100*abs(CorrCoeff(k))),'color','w')
            end
        end

        CorticalScouts.CorrCoefThres = CorrCoefThres;
        CorticalScouts.CorrRefChan = CorrRefChan;
        CorticalScouts.CorrTimeWin = CorrTimeWin;

        %CorrCoefThres

        % Now generate cortical scout file

        % What's the name of the current cortical envelope ?
        ActiveTess = get(hScoutsManagerFig.removed,'String'); % Find the active Cortical surface
        iCortex = get(hScoutsManagerFig.removed,'Value');
        if iscell(ActiveTess)
            ActiveTess= ActiveTess{iCortex};
        end

        % XYZ Coordinates of the scouts
        Visu = get(DATAPLOT,'Userdata');
        cd(Users.SUBJECTS)
        load(Visu.Tesselation,'Comment','Vertices')
        % What's the current surface ?
        imesh = find(strcmp(Comment,ActiveTess));
        Vertices = Vertices{imesh};
        CorticalScouts.Handle = Vertices(:,CorticalScouts.Vertex)';
        clear Vertices
        for k =1 : length(CorticalScouts.Vertex)
            CorticalScouts.HandleLabels{k} = int2str(k);
        end

        if 0%length( CorticalScouts.HandleLabels) == 1
            % Load specific cortical scout file (depth electrode)
            DepthScouts = load('I:\Data\Studies\Epilepsie\02May02\DepthElectrodes_Scouts.mat');
            % Find scout with same name
            ScoutRef = find(strcmpi(CorrRefChanName,cellstr(char(DepthScouts.CorticalScouts.HandleLabels{:}))));
            % Add to current Cortical Scout File
            CorticalScouts.Handle = [CorticalScouts.Handle; DepthScouts.CorticalScouts.Handle(ScoutRef,:)];
            CorticalScouts.HandleLabels{end+1} = DepthScouts.CorticalScouts.HandleLabels{ScoutRef};
            CorticalScouts.Vertex(end+1) = DepthScouts.CorticalScouts.Vertex(ScoutRef);
            Dist = 1000*norm(diff(CorticalScouts.Handle)); % Distance in mm
            sprintf('Distance between depth electrode and MaxCorr spot : %3.2f',Dist)
        end

        % What's the name of the current data set ?
        ResultFiles = get(hScoutsManagerFig.ResultFiles,'String');
        ResultFile = ResultFiles{get(hScoutsManagerFig.ResultFiles,'Value')};

        cd(Users.STUDIES)
        dirr = fileparts(Users.CurrentData.StudyFile);
        cd(dirr);

        % Create Cortical Scout File
        [filename, pathname] = uiputfile(['CorrCoefScouts_',get(hScoutsManagerFig.TruncateFactor,'string'),'.mat'], 'Save Cortical Scout in...');
        save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat');

        % Visualization
        dataplot_cb('LoadCorticalSpot',fullfile(pathname,filename))

        %----------------------------------------------------------------------------

    case 'CorticalScoutFromThres' % Create a cortical scout file with areas above a given %-threshold
        data.Results.Display.Handles.hPatch  = findobj(0,'tag','tessellation_window');
        CorticalScouts = get(data.Results.Display.Handles.hPatch,'Userdata');
        ScoutsManagerFig = findobj(0,'Tag','tesselation_select');
        hScoutsManagerFig = guihandles(ScoutsManagerFig);

        % Let's do it simple first
        Results = get(hScoutsManagerFig.ResultFiles,'Userdata');
        M = max(abs(Results.ImageGridAmp),[],2); % Take maximum over time
        MAX = max(M);
        cThres = str2num(get(hScoutsManagerFig.TruncateFactor,'string'))/100;

        % Indices of the sources above threshold
        CorticalScouts.Vertex = find(M >= cThres*MAX);
        % What's the name of the current cortical envelope ?
        ActiveTess = get(hScoutsManagerFig.removed,'String'); % Find the active Cortical surface
        iCortex = get(hScoutsManagerFig.removed,'Value');
        if iscell(ActiveTess)
            ActiveTess= ActiveTess{iCortex};
        end

        % XYZ Coordinates of the scouts
        Visu = get(DATAPLOT,'Userdata');
        cd(Users.SUBJECTS)
        load(Visu.Tesselation,'Comment','Vertices')
        % What's the current surface ?
        imesh = find(strcmp(Comment,ActiveTess));
        Vertices = Vertices{imesh};
        CorticalScouts.Handle = Vertices(:,CorticalScouts.Vertex)';
        clear Vertices
        for k =1 : length(CorticalScouts.Vertex)
            CorticalScouts.HandleLabels{k} = int2str(k);
        end

        % What's the name of the current data set ?
        ResultFiles = get(hScoutsManagerFig.ResultFiles,'String');
        ResultFile = ResultFiles{get(hScoutsManagerFig.ResultFiles,'Value')};

        cd(Users.STUDIES)
        dirr = fileparts(Users.CurrentData.StudyFile);
        cd(dirr);

        % Create Cortical Scout File
        [filename, pathname] = uiputfile(['CorticalScoutFromThresh_',get(hScoutsManagerFig.TruncateFactor,'string'),'.mat'], 'Save Cortical Scout in...');
        save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat');

        % Visualization
        dataplot_cb('LoadCorticalSpot',fullfile(pathname,filename))

    end

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