Another one on "Structure assignment to non-structure object."

The error happens at line 66:

Subject 002_S_0295_2012-05-10

Structure assignment to non-structure object.

Error in map_rest_data_to_power264_Copy (line 66)

sampMask(iRoi).roi = distMat < sphere_radius_mm/voxel_sz + shellThickness/voxel_sz;

And here is the code:

1   % Map output of SPM preprocessing to Power's 264 Nodes parcellation scheme
2   clearvars;
3   % close all;
4   clc
5
6
7   % Input data path
8   data_path = 'E:/ADNI/Preprocessed_test/FunImgARWS/';
9   output_dir = 'E:/ADNI/Preprocessed_test/Output/';
10
11   % Get list of all subjects
12   list_subj = dir([data_path,'00*']);
13  nSubj = length(list_subj);
14  nscans = 6720; 
15  d =264; % this is the number of nodes in Power template
16
17  % Read the 264 ROI positions defined by Power
18  [numval_power,txt,raw] = xlsread('C:/Users/dkarletsos/Box Sync/Tulane/TCBG/AD/issues with preprocessing/biao_voxels/mmc2.xls');
19
20  
21   
22
23  for iSubj =1:nSubj
24      %     tic
25      if(~exist([output_dir,'rest_',list_subj(iSubj).name,'.mat'],'file'))
26          if(exist([data_path,list_subj(iSubj).name],'dir'))
27              
28              nii_path = [data_path,list_subj(iSubj).name,'/'];
29              
30              if(exist([nii_path,'rp_scan_001.txt'],'file'))
31                  
32                  fprintf('Subject %s\n',list_subj(iSubj).name);
33                  
34                  % Read all 3d nii files
35                  list_nii = dir([nii_path,'swra*.nii']);
36                  
37                  % read motion values
38                  if(exist([nii_path,'rp_scan_001.txt'],'file'))
39                      motion_val = dlmread([nii_path,'rp_scan_001.txt']);
40                      motion_val = motion_val-repmat(mean(motion_val),[size(motion_val,1),1]);
41                  else
42                      error('Motion file could not be read!');
43                  end
44                  
45                  % Compute image grid (check according to SPM output dimensions)
46                  [xMat,yMat,zMat] = ndgrid(1:61,1:73,1:61);
47                  
48                  % Initialize array to store time-serie data % not sure what
49                  % the 70 figure is
50                  img_time_serie = zeros(264,140,length(list_nii));
51                  
52                  % convert MNI coordinates to voxel grid coordinates
53                  vox_idx = mm2vox(numval_power(:,2:4),[nii_path,list_nii(1).name]);
54                
55                  sphere_radius_mm = 5; %  radius spheres
56                  voxel_sz = 2; % voxels are 2x2x2mm
57                  
58                  sampMask = cell(size(numval_power,1));
59                
60                  % Get i for each ROI
61                  for iRoi =1:size(numval_power,1)
62                      c = vox_idx(iRoi,:); % XYZ of center of sphere
63                      distMat = sqrt((xMat-c(1)).^2 + (yMat-c(2)).^2 + (zMat-c(3)).^2);
64                      shellThickness = 0.1; % Ie, only sample pixels within shellThickness-mm of a perfect sphere
65                      %sampMask{iRoi} = distMat  < sphere_radius_mm/voxel_sz + shellThickness/voxel_sz;
66                      sampMask(iRoi).roi = distMat  < sphere_radius_mm/voxel_sz + shellThickness/voxel_sz;
67                      % 
68                      %                      sampMask{iRoi} = abs(distMat - sphere_radius_mm/voxel_sz) < shellThickness/voxel_sz;
69                  end  % end ROI
70                                  
71                  % Loop through each scan
72                  dat_4d_full = zeros(61,73,61,length(list_nii));
73                  for iScan =1:length(list_nii)                    
74                      nii_img = load_nii([nii_path,list_nii(iScan).name]);
75                      dat_4d_full(:,:,:,iScan) = nii_img.img;
76                  end
77                  % Loop through each ROI
78                  for iRoi =1:size(numval_power,1)                
79                      sampPx = dat_4d_full(repmat(logical(sampMask{iRoi}),[1,1,1,nscans]));
80                      sampPx = reshape(sampPx,[nnz(sampMask{iRoi}),nscans])';
81                      
82                      % Detrend data (in time)
83                      Xtrend = [ones(nscans,1),[1:nscans]',([1:nscans].^2)'];
84                      for i_vox =1:size(sampPx,2)
85                           b = regress(sampPx(:,i_vox),Xtrend);
86                           sampPx(:,i_vox) = sampPx(:,i_vox) - Xtrend*b;
87                      end
88                      
89                      % Whiten data
70                      [Xwh, mu, invMat, whMat] = whiten(sampPx);
71                      img_time_serie(iRoi,:,:) = Xwh';
72                  end
73                  
74                  % Regress effect of motion
75                  img_time_serie = img_time_serie -repmat(mean(img_time_serie,2),[1,size(img_time_serie,2)]);
76                  img_time_serie = img_time_serie';
77                  img_time_serie_moco = zeros(size(img_time_serie));
78                  for iRoi =1:size(img_time_serie,2)
79                      b = regress(img_time_serie(:,iRoi),motion_val);
80                      img_time_serie_moco(:,iRoi) = img_time_serie(:,iRoi) -  motion_val*b;
81                  end
82                  img_time_serie = img_time_serie_moco';
83                  %%
84  %                 % Filter data using band pass butterworth filter
85  %                 img_time_serie = img_time_serie -repmat(mean(img_time_serie,2),[1,size(img_time_serie,2)]);
86 %                 lowFreq =0.01;
87 %                 hiFreq =0.1;
88 %                 fs =1/3;
89 %                 order = 5;
90 %                 [b,a] = butter(order, [lowFreq hiFreq]/(fs/2), 'bandpass');
91 %                 img_time_serie = filter(b,a,img_time_serie,[],2);
92 %                 
93 % %                                     % correlation matrix
94 % %                                     RHO = corr(img_time_serie');
95 % %                                     figure()
96 % %                                     subplot(121),imagesc(RHO)
97 % %                                     subplot(122),histogram(RHO(:))
98                 %%
99                 save([output_dir,'/rest_',list_subj(iSubj).name,'.mat'],'img_time_serie','motion_val');
100             end
101         end
102     end
103     %     toc
104 end

[Geoff Hayes]

Dimitris - why are you considering sampMask(iRoi) to be a structure with a field called roi when it is really just a cell within a cell array? Why not just do

sampMask(iRoi) = distMat  < sphere_radius_mm/voxel_sz + shellThickness/voxel_sz;

?

[Dimitris Karletsos]

By doing so, I get:

Subject 002_S_0295_2012-05-10

Conversion to cell from logical is not possible.

Error in map_rest_data_to_power264_Copy (line 66)

sampMask(iRoi) = distMat < sphere_radius_mm/voxel_sz + shellThickness/voxel_sz;

[Walter Roberson]

sampMask{iRoi} = distMat  < sphere_radius_mm/voxel_sz + shellThickness/voxel_sz;

[Dimitris Karletsos]

got it, thanks.