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14 | 14 |
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15 | 15 | %% ASSUMPTION |
16 | 16 | % |
17 | | -% This assumes that the 2 immages are in the same space (MNI, individual) |
| 17 | +% This assumes that the 2 images are in the same space (MNI, individual) |
18 | 18 | % but they might not necessarily have the same resolution. |
19 | 19 | % |
20 | 20 | % In SPM lingo this means they are coregistered but not necessarily resliced. |
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29 | 29 | % You can use the resliceRoiImages for that. |
30 | 30 |
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31 | 31 | %% |
32 | | -zMap = fullfile(pwd, 'inputs', 'visual motion_association-test_z_FDR_0.01.nii'); |
| 32 | +zMap = fullfile(pwd, 'inputs', 'visual_motion_association-test_z_FDR_0.01.nii'); |
33 | 33 | dataImage = fullfile(pwd, 'inputs', 'TStatistic.nii'); |
34 | 34 |
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35 | 35 | opt.unzip.do = true; |
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44 | 44 | % all of these functions can be found below and show you how to create ROIs and |
45 | 45 | % / or ROIs to extract data from an image. |
46 | 46 | % |
47 | | -[roiName, zMap] = preprareDataAndROI(opt, dataImage, zMap); |
| 47 | +[roiName, zMap] = prepareDataAndROI(opt, dataImage, zMap); |
48 | 48 |
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49 | 49 | data_mask = getDataFromMask(dataImage, roiName); |
50 | 50 | data_sphere = getDataFromSphere(opt, dataImage); |
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136 | 136 |
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137 | 137 | %% HELPER FUNCTION |
138 | 138 |
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139 | | -function [roiName, zMap] = preprareDataAndROI(opt, dataImage, zMap) |
| 139 | +function [roiName, zMap] = prepareDataAndROI(opt, dataImage, zMap) |
140 | 140 |
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141 | 141 | if opt.unzip.do |
142 | 142 | gunzip(fullfile('inputs', '*.gz')); |
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