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%--brain mask with the brain tissue
mask_name =
'C:\Users\Administrator\Desktop\workspace\preprocessed\masks\within_brain_mask.nii'
;
M = load_untouch_nii( mask_name ); % load mask NIFTI
mask =
double
(M.img>
0
); % get 3d v
%--brain functional 4d data
data_4d =
'C:\Users\Administrator\Desktop\workspace\preprocessed\4d\func_3d.nii'
;
% data_4d =
'C:\Users\Administrator\Desktop\phycaa_workspace\phycaa_plus_2104_03_27\_PHYCAA_step1+2.nii'
;
V = load_untouch_nii( data_4d );
%--transform 4d array to 2d array, using brain_mask
within_brain_voxels = nifti_to_mat(V,M);
nt_matrix = within_brain_voxels;
[V_c S_c temp] = svd( nt_matrix' * nt_matrix );
% PC-space representation
Q_c = V_c * sqrt( S_c );
offSet=
1
;
pcs=
4
;
% estimate temporal autocorrelation maximized
"sources"
Q1 = Q_c(
1
:(end-offSet) ,
1
:pcs ); % un-offset
Q2 = Q_c( (offSet+
1
):end ,
1
:pcs ); % offsetted timeseries
% canonical correlations on time-lagged data
[A,B,R,U,V,stats] = canoncorr(Q1,Q2);
% getting stable
"average"
autocorrelated timeseries
a=[U(
1
,:)]; b=[U(
2
:end,:) + V(
1
:end-
1
,:)./
2
]; c=[V(end,:)];
tset = [a;b;c];
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本文转自二郎三郎博客园博客，原文链接：http://www.cnblogs.com/haore147/p/3797817.html，如需转载请自行联系原作者
