SVMCrossVal.git

@@ -3,6 +3,8 @@ function outputStruct = calculateDecodePerformance(inputStruct,SubjectID)

 addpath 'libsvm-mat-2.88-1';

+SINGLE = 1;

+

 outputStruct = struct;

 namehelper      = strcat('s',SubjectID);

@@ -66,6 +68,8 @@ maxPerformance = -inf;

             svmdata      = tmp(:,2:size(tmp,2));

             svmlabel     = tmp(:,1);

+            

+            if SINGLE

                 performance  = svmtrain(svmlabel, svmdata, svmargs);

                 minPerformance = min(minPerformance,performance);

@@ -74,221 +78,13 @@ maxPerformance = -inf;

                 decodePerformance = [decodePerformance; performance];

             end

+        end

+        

         outputStruct.decodePerformance  = decodePerformance;

         outputStruct.svmdata            = svmdata;

         outputStruct.svmlabel           = svmlabel;

         outputStruct.rawTimeCourse      = pst;

         outputStruct.minPerformance     = minPerformance;

         outputStruct.maxPerformance     = maxPerformance;

-

-% display(sprintf('Min CrossVal Accuracy: %g%% \t Max CrossVal Accuracy: %g%%',minPerformance,maxPerformance));

-end

-

-

-function extr = calculateImageData(voxelList,des,smoothed)

-

-dtype='PSTH';

-

-switch dtype 

-    case 'PSTH'

-        V=des.xY.VY;

-    case 'betas'

-        V=des.Vbeta;

-end;

-

-if V(1).fname(1)~='D'

-     for z=1:length(V) % Change Drive Letter!\

-      	V(z).fname(1) = 'D';

-     end; 

-end

-

-if (~smoothed)

-  for z=1:length(V) % Change Drive Letter!\

-      % D:....SUBJECTID\session\swfanders...

-      % D:....SUBJECTID\session\wfanders...

-      tmp = findstr(filesep,V(z).fname);

-      V(z).fname = strcat(V(z).fname(1:tmp(end)),V(z).fname(tmp(end)+2:end));

-  end;

-end

-

-% rad = 0; % one voxel

-% opt = 1; % xyz coordinates [mm]

-

-

-vox = voxelList;

-nRoi = size(vox,1);

-

-nImg = numel(V);

-

-for k=1:nImg

-	extr(k) = struct(...

-        'val',   repmat(NaN, [1 nRoi]),...

-		'mean',  repmat(NaN, [1 nRoi]),...

-		'sum',   repmat(NaN, [1 nRoi]),...

-		'nvx',   repmat(NaN, [1 nRoi]),...

-		'posmm', repmat(NaN, [3 nRoi]),...

-		'posvx', repmat(NaN, [3 nRoi]));

-

-    roicenter = round(inv(V(k).mat)*[vox, ones(nRoi,1)]');

-

-	for l = 1:nRoi

-

-%         if rad==0

-            x = roicenter(1,l);

-            y = roicenter(2,l);

-            z = roicenter(3,l);

-%         else

-%             tmp = spm_imatrix(V(k).mat);

-%             vdim = tmp(7:9);

-%             vxrad = ceil((rad*ones(1,3))./(ones(nRoi,1)*vdim))';

-%             [x y z] = ndgrid(-vxrad(1,l):sign(vdim(1)):vxrad(1,l), ...

-%                       -vxrad(2,l):sign(vdim(2)):vxrad(2,l), ...

-%                       -vxrad(3,l):sign(vdim(3)):vxrad(3,l));

-%             sel = (x./vxrad(1,l)).^2 + (y./vxrad(2,l)).^2 + ...

-%                   (z./vxrad(3,l)).^2 <= 1;

-%             x = roicenter(1,l)+x(sel(:));

-%             y = roicenter(2,l)+y(sel(:));

-%             z = roicenter(3,l)+z(sel(:));

-%         end;

-

-

-		dat                 = spm_sample_vol(V(k), x, y, z,0);

-		[maxv maxi]         = max(dat);

-		tmp                 = V(k).mat*[x(maxi); y(maxi); z(maxi);1]; % Max Pos

-		extr(k).val(l)      = maxv;

-		extr(k).sum(l)      = sum(dat);

-		extr(k).mean(l)     = nanmean(dat);

-        extr(k).nvx(l)      = numel(dat);

-		extr(k).posmm(:,l)  = tmp(1:3);

-		extr(k).posvx(:,l)  = [x(maxi); y(maxi); z(maxi)]; % Max Pos

-	end;

-

-end;

 end

-% disp(sprintf('Extracted at %.1f %.1f %.1f [xyz(mm)], average of %i voxel(s) [%.1fmm radius Sphere]',vox,length(x),rad));

-

-function pst = calculatePST(des,globalStart,baselineStart,baselineEnd,globalEnd,eventList,data,sessionList)

-    bstart          = baselineStart;

-    bend            = baselineEnd;

-    edur            = 12;

-    pre             =  globalStart;

-    post            =  globalEnd;

-    res             = 1;

-

-    normz           = 'file';

-    pm              = 0;

-

-    lsess           = getNumberOfScans(des);

-    nSessions       = getNumberOfSessions(des);

-    tr              = 2;

-

-    [evntrow evntcol]=size(eventList);

-    

-

-    hsec=str2num(des.xsDes.High_pass_Filter(8:end-3)); % Highpass filter [sec] from SPM.mat

-

-    if strcmp(des.xBF.UNITS,'secs')

-        unitsecs=1;

-    end;

-

-    nScansPerSession=getNumberOfScans(des);

-    %stime=[0:tr:max(nScansPerSession)*tr+post-tr]; % Stimulus time for raw data plot

-    stime=0:tr:max(nScansPerSession)*tr+round(post/tr)*tr-tr; % Stimulus time for raw data plot

-

-

-

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

-    % RUN

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

-

-

-    % Digital Highpass

-    Rp=0.5;

-    Rs=20;

-    NO=1;

-    Wp=1/((1/2/tr)/(1/hsec));

-    [B, A] = ellip(NO,Rp,Rs,Wp,'high');

-

-    sdata(1:max(nScansPerSession)+round(post/tr),1:nSessions)=nan; % Open Data Matrix

-    for z=1:nSessions % Fill Data Matrix sessionwise

-        sdata(1:nScansPerSession(z),z)=data(sum(nScansPerSession(1:z))-nScansPerSession(z)+1:sum(nScansPerSession(1:z)))';

-    end;

-%         usdata=sdata; % Keep unfiltered data

-

-    sdatamean=nanmean(nanmean(sdata(:,:)));

-    for z=1:nSessions

-%             X(:,z)=[1:1:max(nScansPerSession)]'; % #Volume

-        sdata(1:nScansPerSession(z),z)=filtfilt(B,A,sdata(1:nScansPerSession(z),z)); %Filter Data (Highpass)

-    end;

-    sdata=sdata+sdatamean;

-

-

-    %%%%Parametric Modulation Modus%%%%

-    if pm %Find Parameters for Event of Interest

-        [imods modss mods erow evntrow eventList] = getParametricMappingEvents(eventList,evntrow,des,pmf);

-    end;

-    %%%%PM%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

-

-

-    for zr=1:evntrow

-        n{zr}=0;

-        nn{zr}=0; 

-        nnn{zr}=0;

-        sstart{zr}=1;

-    end;

-

-

-    sesst0=0; 

-    for sessionID=sessionList

-        if sessionID>1

-            sesst0(sessionID)=sum(lsess(1:sessionID-1))*tr;  

-        end;

-        for zr=1:evntrow  %LABEL NUMBER, EVENT GROUP

-            sstart{zr}=n{zr}+1;

-            for ze=1:evntcol % EVENT INDEX in EventList

-                if ze==1 || (ze>1 && eventList(zr,ze)~=eventList(zr,ze-1))

-                    for zz=1:length(des.Sess(sessionID).U(eventList(zr,ze)).ons) % EVENT REPETITION NUMBER

-                        if ~unitsecs

-                            des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)=(des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)-1)*tr;

-                            des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)=(des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)-1)*tr;

-                        end;

-

-                        nnn{zr}=nnn{zr}+1; % INFO for rawdataplot start

-                        if des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)<edur

-                            mev{zr}(nnn{zr},1:2)=[des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+sesst0(sessionID) edur]; % modeled event [onset length]

-                        else

-                            mev{zr}(nnn{zr},1:2)=[des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+sesst0(sessionID) des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)];

-                        end; % INFO for rawdataplot end

-

-                        n{zr}=n{zr}+1;

-                        pst{zr}(n{zr},:)=interp1(stime,sdata(:,sessionID),[des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+pre:res:des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+post],'linear');

-                        if strcmp(normz,'epoc')

-                            bline=nanmean(pst{zr}(n{zr},round(-pre/res+(bstart)/res+1):round(-pre/res+(bend)/res+1)));

-                            if isnan(bline)

-                                pst{zr}(n{zr},1:-pre/res+post/res+1)=nan;

-                            else

-%                                     nn{zr}=nn{zr}+1;

-                                pst{zr}(n{zr},:)=(pst{zr}(n{zr},:)-bline)/bline*100; % 'epoch-based' normalization

-                            end;

-                        end;

-                    end;

-                end;

-            end;

-            if ~strcmp(normz,'epoc')

-                bline(zr)=nanmean(nanmean(pst{zr}(sstart{zr}:n{zr},-pre/res+(bstart)/res+1:-pre/res+(bend)/res+1)));

-                bstd(zr)=nanmean(nanstd(pst{zr}(sstart{zr}:n{zr},-pre/res+(bstart)/res+1:-pre/res+(bend)/res+1)));

-                nn{zr}=n{zr};

-            end;

-        end;

-        if strcmp(normz,'filz')

-            for zr=1:evntrow

-                pst{zr}(sstart{zr}:n{zr},:)=(pst{zr}(sstart{zr}:n{zr},:)-mean(bline))/mean(bstd); % session-based z-score normalization

-            end;

-        elseif strcmp(normz,'file')

-            for zr=1:evntrow

-                pst{zr}(sstart{zr}:n{zr},:)=(pst{zr}(sstart{zr}:n{zr},:)-mean(bline))/mean(bline)*100; % session-based normalization

-            end;

-        end;

-    end;

-end

@@ -36,9 +36,6 @@ end

         calculateParams.eventList       = classStruct.eventMatrix; %[9,11,13; 10,12,14];

 %         calculateParams.eventList       = getPSTEventMatrix(calculateParams.labelMap);

-%         params = struct;

-%         params.nClasses = 2;

-        

         subjectSelection = getSubjectIDString(paramModel);

         decode = struct;

         decode.decodePerformance = [];

@@ -53,13 +50,11 @@ end

             display('... done.');

             %% calculate

-            display(sprintf('calculating cross-validation performance time-shift for Subject %s. Please Wait. ...',SubjectID));

             calculateParams.(namehelper).des             = spm.SPM;

             calculateParams.(namehelper).voxelList       = parseVoxelList(paramModel,SubjectID);

-            

             assignin('base','calculateParams',calculateParams);

-    %         [decodeTable rawTimeCourse] = calculateDecodePerformance(spm,params.frameShiftStart,params.frameShiftEnd,params.xTimeWindow,params.svmopts,1:4,params.sessionList,params.voxelList,params.classList,params.labelMap,params.normalize);

+            display(sprintf('calculating cross-validation performance time-shift for Subject %s. Please Wait. ...',SubjectID));

             display('switching off all warnings');

             warning_state               = warning('off','all');

             display('calculating ...');

@@ -71,9 +66,6 @@ end

             decode.decodePerformance    = [decode.decodePerformance decode.(namehelper).decodePerformance];

             decode.rawTimeCourse        = [decode.rawTimeCourse decode.(namehelper).rawTimeCourse];

-            

-%             display(sprintf('Min CrossVal Accuracy: %g%% \t Max CrossVal Accuracy: %g%%',decode.minPerformance,decode.maxPerformance));

-

             assignin('base','decode',decode);

         end

@@ -0,0 +1,80 @@

+function extr = calculateImageData(voxelList,des,smoothed)

+

+dtype='PSTH';

+

+switch dtype 

+    case 'PSTH'

+        V=des.xY.VY;

+    case 'betas'

+        V=des.Vbeta;

+end;

+

+if V(1).fname(1)~='D'

+     for z=1:length(V) % Change Drive Letter!\

+      	V(z).fname(1) = 'D';

+     end; 

+end

+

+if (~smoothed)

+  for z=1:length(V) % Change Drive Letter!\

+      % D:....SUBJECTID\session\swfanders...

+      % D:....SUBJECTID\session\wfanders...

+      tmp = findstr(filesep,V(z).fname);

+      V(z).fname = strcat(V(z).fname(1:tmp(end)),V(z).fname(tmp(end)+2:end));

+  end;

+end

+

+% rad = 0; % one voxel

+% opt = 1; % xyz coordinates [mm]

+

+

+vox = voxelList;

+nRoi = size(vox,1);

+

+nImg = numel(V);

+

+for k=1:nImg

+	extr(k) = struct(...

+        'val',   repmat(NaN, [1 nRoi]),...

+		'mean',  repmat(NaN, [1 nRoi]),...

+		'sum',   repmat(NaN, [1 nRoi]),...

+		'nvx',   repmat(NaN, [1 nRoi]),...

+		'posmm', repmat(NaN, [3 nRoi]),...

+		'posvx', repmat(NaN, [3 nRoi]));

+

+    roicenter = round(inv(V(k).mat)*[vox, ones(nRoi,1)]');

+

+	for l = 1:nRoi

+

+%         if rad==0

+            x = roicenter(1,l);

+            y = roicenter(2,l);

+            z = roicenter(3,l);

+%         else

+%             tmp = spm_imatrix(V(k).mat);

+%             vdim = tmp(7:9);

+%             vxrad = ceil((rad*ones(1,3))./(ones(nRoi,1)*vdim))';

+%             [x y z] = ndgrid(-vxrad(1,l):sign(vdim(1)):vxrad(1,l), ...

+%                       -vxrad(2,l):sign(vdim(2)):vxrad(2,l), ...

+%                       -vxrad(3,l):sign(vdim(3)):vxrad(3,l));

+%             sel = (x./vxrad(1,l)).^2 + (y./vxrad(2,l)).^2 + ...

+%                   (z./vxrad(3,l)).^2 <= 1;

+%             x = roicenter(1,l)+x(sel(:));

+%             y = roicenter(2,l)+y(sel(:));

+%             z = roicenter(3,l)+z(sel(:));

+%         end;

+

+

+		dat                 = spm_sample_vol(V(k), x, y, z,0);

+		[maxv maxi]         = max(dat);

+		tmp                 = V(k).mat*[x(maxi); y(maxi); z(maxi);1]; % Max Pos

+		extr(k).val(l)      = maxv;

+		extr(k).sum(l)      = sum(dat);

+		extr(k).mean(l)     = nanmean(dat);

+        extr(k).nvx(l)      = numel(dat);

+		extr(k).posmm(:,l)  = tmp(1:3);

+		extr(k).posvx(:,l)  = [x(maxi); y(maxi); z(maxi)]; % Max Pos

+	end;

+

+end;

+end

\ No newline at end of file

@@ -0,0 +1,124 @@

+function pst = calculatePST(des,globalStart,baselineStart,baselineEnd,globalEnd,eventList,data,sessionList)

+    bstart          = baselineStart;

+    bend            = baselineEnd;

+    edur            = 12;

+    pre             =  globalStart;

+    post            =  globalEnd;

+    res             = 1;

+

+    normz           = 'file';

+    pm              = 0;

+

+    lsess           = getNumberOfScans(des);

+    nSessions       = getNumberOfSessions(des);

+    tr              = 2;

+

+    [evntrow evntcol]=size(eventList);

+    

+

+    hsec=str2num(des.xsDes.High_pass_Filter(8:end-3)); % Highpass filter [sec] from SPM.mat

+

+    if strcmp(des.xBF.UNITS,'secs')

+        unitsecs=1;

+    end;

+

+    nScansPerSession=getNumberOfScans(des);

+    %stime=[0:tr:max(nScansPerSession)*tr+post-tr]; % Stimulus time for raw data plot

+    stime=0:tr:max(nScansPerSession)*tr+round(post/tr)*tr-tr; % Stimulus time for raw data plot

+

+

+

+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

+    % RUN

+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

+

+

+    % Digital Highpass

+    Rp=0.5;

+    Rs=20;

+    NO=1;

+    Wp=1/((1/2/tr)/(1/hsec));

+    [B, A] = ellip(NO,Rp,Rs,Wp,'high');

+

+    sdata(1:max(nScansPerSession)+round(post/tr),1:nSessions)=nan; % Open Data Matrix

+    for z=1:nSessions % Fill Data Matrix sessionwise

+        sdata(1:nScansPerSession(z),z)=data(sum(nScansPerSession(1:z))-nScansPerSession(z)+1:sum(nScansPerSession(1:z)))';

+    end;

+%         usdata=sdata; % Keep unfiltered data

+

+    sdatamean=nanmean(nanmean(sdata(:,:)));

+    for z=1:nSessions

+%             X(:,z)=[1:1:max(nScansPerSession)]'; % #Volume

+        sdata(1:nScansPerSession(z),z)=filtfilt(B,A,sdata(1:nScansPerSession(z),z)); %Filter Data (Highpass)

+    end;

+    sdata=sdata+sdatamean;

+

+

+    %%%%Parametric Modulation Modus%%%%

+    if pm %Find Parameters for Event of Interest

+        [imods modss mods erow evntrow eventList] = getParametricMappingEvents(eventList,evntrow,des,pmf);

+    end;

+    %%%%PM%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

+

+

+    for zr=1:evntrow

+        n{zr}=0;

+        nn{zr}=0; 

+        nnn{zr}=0;

+        sstart{zr}=1;

+    end;

+

+

+    sesst0=0; 

+    for sessionID=sessionList

+        if sessionID>1

+            sesst0(sessionID)=sum(lsess(1:sessionID-1))*tr;  

+        end;

+        for zr=1:evntrow  %LABEL NUMBER, EVENT GROUP

+            sstart{zr}=n{zr}+1;

+            for ze=1:evntcol % EVENT INDEX in EventList

+                if ze==1 || (ze>1 && eventList(zr,ze)~=eventList(zr,ze-1))

+                    for zz=1:length(des.Sess(sessionID).U(eventList(zr,ze)).ons) % EVENT REPETITION NUMBER

+                        if ~unitsecs

+                            des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)=(des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)-1)*tr;

+                            des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)=(des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)-1)*tr;

+                        end;

+

+                        nnn{zr}=nnn{zr}+1; % INFO for rawdataplot start

+                        if des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)<edur

+                            mev{zr}(nnn{zr},1:2)=[des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+sesst0(sessionID) edur]; % modeled event [onset length]

+                        else

+                            mev{zr}(nnn{zr},1:2)=[des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+sesst0(sessionID) des.Sess(sessionID).U(eventList(zr,ze)).dur(zz)];

+                        end; % INFO for rawdataplot end

+

+                        n{zr}=n{zr}+1;

+                        pst{zr}(n{zr},:)=interp1(stime,sdata(:,sessionID),[des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+pre:res:des.Sess(sessionID).U(eventList(zr,ze)).ons(zz)+post],'linear');

+                        if strcmp(normz,'epoc')

+                            bline=nanmean(pst{zr}(n{zr},round(-pre/res+(bstart)/res+1):round(-pre/res+(bend)/res+1)));

+                            if isnan(bline)

+                                pst{zr}(n{zr},1:-pre/res+post/res+1)=nan;

+                            else

+%                                     nn{zr}=nn{zr}+1;

+                                pst{zr}(n{zr},:)=(pst{zr}(n{zr},:)-bline)/bline*100; % 'epoch-based' normalization

+                            end;

+                        end;

+                    end;

+                end;

+            end;

+            if ~strcmp(normz,'epoc')

+                bline(zr)=nanmean(nanmean(pst{zr}(sstart{zr}:n{zr},-pre/res+(bstart)/res+1:-pre/res+(bend)/res+1)));

+                bstd(zr)=nanmean(nanstd(pst{zr}(sstart{zr}:n{zr},-pre/res+(bstart)/res+1:-pre/res+(bend)/res+1)));

+                nn{zr}=n{zr};

+            end;

+        end;

+        if strcmp(normz,'filz')

+            for zr=1:evntrow

+                pst{zr}(sstart{zr}:n{zr},:)=(pst{zr}(sstart{zr}:n{zr},:)-mean(bline))/mean(bstd); % session-based z-score normalization

+            end;

+        elseif strcmp(normz,'file')

+            for zr=1:evntrow

+                pst{zr}(sstart{zr}:n{zr},:)=(pst{zr}(sstart{zr}:n{zr},:)-mean(bline))/mean(bline)*100; % session-based normalization

+            end;

+        end;

+    end;

+end

\ No newline at end of file

@@ -15,6 +15,8 @@ function spm_SVMCrossVal

     set(frame,'Units','normalize');

+    savemenu = uimenu(frame,'Label','Save/Load');

+    

     model.subjectMap = SubjectRoiMapping;

     nElementRows = 24;

     optionLineHeight = 1.0/nElementRows;

@@ -39,6 +41,8 @@ function spm_SVMCrossVal

     set(model.subjectSelector,'BackgroundColor','w');

     model.txtSmoothed     = createTextField(pSubject,[0.68*frameWidth firstRow  0.25*frameWidth controlElementHeight],'1');

+    model.txtMultisubject = createTextField(pSubject,[0.68*frameWidth firstRow*2  0.25*frameWidth controlElementHeight],'single');

+    set(model.txtMultisubject,'enable','off');

     % PSTH

     firstColumn  = 5.00;

@@ -60,12 +64,12 @@ function spm_SVMCrossVal

     lFramsSize  = createLabel(pPSTH, [firstColumn  fifthRow  0.33*frameWidth controlElementHeight],'SVM Frame Size');

-    model.txtBaselineStart   = createTextField(pPSTH,[secondColumn thirdRow  0.25*frameWidth controlElementHeight],'-22.0');

-    model.txtBaselineEnd     = createTextField(pPSTH,[thirdColumn  thirdRow  0.25*frameWidth controlElementHeight],'-20.0');

-    model.txtPSTHStart       = createTextField(pPSTH,[secondColumn secondRow 0.25*frameWidth controlElementHeight],'-25.0');

-    model.txtPSTHEnd         = createTextField(pPSTH,[thirdColumn  secondRow 0.25*frameWidth controlElementHeight],' 20.0');

-    model.txtFrameShiftStart = createTextField(pPSTH,[secondColumn fourthRow 0.25*frameWidth controlElementHeight],'-20.0');

-    model.txtFrameShiftEnd   = createTextField(pPSTH,[thirdColumn  fourthRow 0.25*frameWidth controlElementHeight],' 15.0');

+    model.txtPSTHStart       = createTextField(pPSTH,[secondColumn secondRow 0.25*frameWidth controlElementHeight],'-1.0');

+    model.txtPSTHEnd         = createTextField(pPSTH,[thirdColumn  secondRow 0.25*frameWidth controlElementHeight],' 35.0');

+    model.txtBaselineStart   = createTextField(pPSTH,[secondColumn thirdRow  0.25*frameWidth controlElementHeight],'-3.0');

+    model.txtBaselineEnd     = createTextField(pPSTH,[thirdColumn  thirdRow  0.25*frameWidth controlElementHeight],'-1.0');

+    model.txtFrameShiftStart = createTextField(pPSTH,[secondColumn fourthRow 0.25*frameWidth controlElementHeight],'-5.0');

+    model.txtFrameShiftEnd   = createTextField(pPSTH,[thirdColumn  fourthRow 0.25*frameWidth controlElementHeight],' 45.0');

     model.txtFrameShiftDur   = createTextField(pPSTH,[secondColumn fifthRow  0.25*frameWidth controlElementHeight],' 0');

@@ -107,63 +111,58 @@ function spm_SVMCrossVal

     set(model.txtSVMopts,'HorizontalAlignment','left');

     set(btnRunButton,'Callback',{@cbRunSVM,model}); % set here, because of model.    

+    uimenu(savemenu,'Label','Save','Callback',{@mcb_save,model});

+    uimenu(savemenu,'Label','Load','Callback',{@mcb_load,model});

+

     set(frame,'Visible','on');

 end

-function label = createLabel(parent,  pos, labelText)

-    label = uicontrol(parent,'Style','text','String',labelText,'Position',pos);

-    set(label,'HorizontalAlignment','left');

-    set(label,'Units','characters');

-%     set(label,'BackgroundColor','r');

-end

+function mcb_save(src,event,model)

+display('SAVE');

-function btn = createButton(parent,pos,tag,labelText,cbArgs)

-    btn = uicontrol(parent,'Position',pos,'String',labelText,'tag',tag);

-     set(btn,'Callback',{@cbParseVariable,cbArgs});

-%     set(btn,'BackgroundColor','b');

 end

-function txt = createTextField(parent,pos,model)

-    txt = uicontrol(parent,'Style','edit','String',model,'Position',pos);

-    set(txt,'BackgroundColor','w');

-end

-

-function drpField = createDropDown(parent,pos,selectionModel)

- drpField = uicontrol(parent,'Style','popupmenu','Position',pos);

-  set(drpField,'String',selectionModel.Strings);

-  set(drpField,'BackgroundColor','w');

+function mcb_load(src,event,model)

+display('LOAD');

 end

 function sane = isSane(model)

+% TODO

 sane = 1;

 end

-

 function cbRunSVM(src,evnt,model)

-

     display('RUN');

-

-    % TODO test parameter values

-    

     if isSane(model)

-        set(0,'userdata',model);

-%         set(src,'Enable','off');

-%         assignin('base','guiParams',model);

         classify(model)

-%         set(src,'Enable','on');

     else

-        %todo error beep!

         error('spmtoolbox:SVMCrossVal:paramcheck','please verify all parameters');

     end

-                                        

 end

-function save(model)

+function label = createLabel(parent,  pos, labelText)

+    label = uicontrol(parent,'Style','text','String',labelText,'Position',pos);

+    set(label,'HorizontalAlignment','left');

+    set(label,'Units','characters');

+%     set(label,'BackgroundColor','r');

+end

+

+function btn = createButton(parent,pos,tag,labelText,cbArgs)

+    btn = uicontrol(parent,'Position',pos,'String',labelText,'tag',tag);

+     set(btn,'Callback',{@cbParseVariable,cbArgs});

+%     set(btn,'BackgroundColor','b');

+end

+function txt = createTextField(parent,pos,model)

+    txt = uicontrol(parent,'Style','edit','String',model,'Position',pos);

+    set(txt,'BackgroundColor','w');

 end

-function model = load()

+function drpField = createDropDown(parent,pos,selectionModel)

+ drpField = uicontrol(parent,'Style','popupmenu','Position',pos);

+  set(drpField,'String',selectionModel.Strings);

+  set(drpField,'BackgroundColor','w');

 end