fMRI预处理batch
fMRI 预处理code 好像暂时用不着
[转自52brain] 原文
addpath('C:/kongliliushuang/ImagingData'); %在这个路径中有SPM包中没有但是你要用的函数，比如spm_get
cwd='C:/kongliliushuang/ImagingData/preprocessing/'; %预处理的工作路径，里面放FunRaw和T1Raw
cd ([cwd,'FunRaw']);
subExpID=dir ('sub0*'); %读取被试编号，此处是在FunRaw这个文件夹下来列出所有被试的编号。这样做的好处是，你的被试编号可以很不规则。
%-----------预处理每一步骤的开关-------如果只想处理某一步，就把开关设为1。当然，前提是这一步所需要的材料已经生成。
creatFolder=1;
convertingFunct=1;convertingStruct=0;
sliceTiming=1;
realignment=1;
coregistration=0;
segmentation=0;
normalization=0;
smoothing=0;
DARTEL_NormSmooth=1; %用DARTEL来进行标准化。如果此处开关打开（设为1），以上convertingStruct, coregistration, segmentation, normalization 和smoothing就应该关上（设为0）。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%% 设置空文件夹装中间步骤数据 %%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if creatFolder
cd (cwd)
mkdir('FunImgF');mkdir('FunImgAF');mkdir('FunImgRAF');mkdir('FunImgWRAF');mkdir('FunImgSWRAF');mkdir('DARTEL_FunImgSWRAF'); %create folders
foldernames={'FunImgF' 'FunImgAF' 'FunImgRAF' 'FunImgWRAF' 'FunImgSWRAF','DARTEL_FunImgSWRAF'};
for folder=1:size(foldernames,2)
folderdir=[ cwd sprintf(foldernames{folder})]
for wnumfolder=1:size(subExpID,1)
cd(folderdir)
mkdir (subExpID(wnumfolder).name);
end
end
cd (cwd)
mkdir('T1Img');
folderdir2=[cwd sprintf('T1Img')]
for wnumfolder=1:size(subExpID,1)
cd(folderdir2)
mkdir (subExpID(wnumfolder).name);
end
cd (cwd)
mkdir('DARTELT1Img');
folderdir2=[cwd sprintf('DARTELT1Img')]
for wnumfolder=1:size(subExpID,1)
cd(folderdir2)
mkdir (subExpID(wnumfolder).name);
end
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
spm_get_defaults % SPM 默认值
global defaults
spm_jobman('initcfg');
nses=1; % sessions或runs的数量
for sub=1:size(subExpID,1)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%% 将DICOM转换成Analyze格式 %%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%convert structural images%%%%%%%%%%%%%%%%%
if convertingStruct
dirStruc=[cwd,'T1Raw/',subExpID(sub).name,'/']; %location of raw DICOM
cd([ cwd,'T1Img/',subExpID(sub).name,'/']); %location to export the Analyze
ds=spm_get('Files',dirStruc,'*.ima') %list all DICOM file names, there is no spm_get inSPM8, but marsbar has that function.
hdrs=spm_dicom_headers(ds); %read DICOM header
spm_dicom_convert(hdrs,'all','flat','img'); % convert
display(sprintf('Anatomical run has been finished.')); % show when finished
end %end of switch
%%%%%%%%%%%%%%%%%%%%convert funtional image%%%%%%%%%%%%%%%%%%%%%%
if convertingFunct
dirFunc=[cwd,'FunRaw/',subExpID(sub).name,'/']; %%location of raw DICOM
cd([cwd,'FunImgF/',subExpID(sub).name,'/']); %location to export the Analyze
df=spm_get('Files',dirFunc,'00*.ima') %list all DICOM file names.
hdr=spm_dicom_headers(df); %read DICOM header
spm_dicom_convert(hdr,'all','flat','img'); %convert
display(sprintf('Functional run has been finished.')); %show when finished
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%% slice timing %%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if sliceTiming
dirst=[cwd,'FunImgF/',subExpID(sub).name,'/'] %location of data to do slice timing (from last step).
st=spm_get('Files',dirst,'fSH*.img') %list all files started with fR
jobs{1}.temporal{1}.st.scans{1}=cellstr(st); %combine all runs, not to slice time seperately. Be careful with {ses}
jobs{1}.temporal{1}.st.nslices = 34;
jobs{1}.temporal{1}.st.tr = 2;
jobs{1}.temporal{1}.st.ta = 2-(2/34);
jobs{1}.temporal{1}.st.so = [1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34]; %34 slices, interleaved, ascending
jobs{1}.temporal{1}.st.refslice = 33; %middle point of time or anatomy. For data collected from SIEMENS,
%the temporal middle point is 33 and 34. The spatial middle point is 17 and 18.
%It should correspond to the "microtime resolution"(also called t) of the 1st level statistical analysis
%and "microtime onset"(also called t0).If there are 33 number of slices, t0=17.
% When reference for slice timing is 33, the 33rd slice is collected the 17th. If the refernce slice is 17, then t0=9.
jobs{1}.temporal{1}.st.prefix = 'a';
spm_jobman('run',jobs); %begin
clear jobs; %clear jobs in this part
diroffile=[cwd,'FunImgF/',subExpID(sub).name,'/'] % do add a / in the end
files=fullfile(diroffile,'afSH*')
diroffile2=[cwd,'FunImgAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy
cd(diroffile)
delete 'af*'
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%% realignment %%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if realignment
cd([cwd,'FunImgSWRAF/',subExpID(sub).name,'/']); %motion pictures exported to the folder of the last step
dir=[cwd,'FunImgAF/',subExpID(sub).name,'/']; %location of files realigned to (from last step)
p=spm_get('Files',dir,'afSH*.img') %list files started with af
jobs{1}.spatial{1}.realign{1}.estwrite.data{1} = cellstr(p); %combine all runs. Be careful with {ses}.
jobs{1}.spatial{1}.realign{1}.estwrite.eoptions.rtm = 0; %set refernce to the first slice
spm_jobman('run',jobs); % run job. motion pictures in the last run folder. mean is in the first run
clear jobs; %clear jobs
diroffile=[cwd,'FunImgAF/',subExpID(sub).name,'/'] %add /
files=fullfile(diroffile,'r*')
files2=fullfile(diroffile,'mean*')
diroffile2=[cwd,'FunImgRAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy
copyfile(files2,diroffile2)
cd(diroffile)
delete 'r*'
delete 'mean*'
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%% coregistration %%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if coregistration
s=spm_get('Files',[cwd,'T1Img/',subExpID(sub).name,'/'],'*.img'); % structural images from DICOM
m=spm_get('Files',[cwd,'FunImgRAF/',subExpID(sub).name,'/'],'mean*.img'); %mean
jobs{1}.spatial{1}.coreg{1}.estimate.ref = cellstr(m); %set mean as the refernce
jobs{1}.spatial{1}.coreg{1}.estimate.source = cellstr(s); % structual image is coregisted to . Mean generated from realignment remains static
spm_jobman('run',jobs);
clear jobs;
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%% segmentation %%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if segmentation
jobs{1}.spatial{1}.preproc.data=cellstr(s); % segment gray/white matter of the structual images
spm_jobman('run',jobs);
clear jobs;
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%% normalization %%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if normalization
s=spm_get('Files',[cwd,'T1Img/',subExpID(sub).name,'/'],'s*.img'); % structural images from DICOM
m=spm_get('Files',[cwd,'FunImgRAF/',subExpID(sub).name,'/'],'mean*.img'); %mean
%%%%%%%%%%%%%%%% normalization of functional images %%%%%%%%%%%%%%%%%%%%%
sp=spm_get('Files',[ cwd,'T1Img/',subExpID(sub).name,'/'],'*seg_sn.mat') %parameters of structual images
sm=spm_get('Files',[ cwd,'T1Img/',subExpID(sub).name,'/'],'m*.img') %path of structual images
jobs{1}.spatial{1}.normalise{1}.write.subj.matname = cellstr(sp); %write parameters
ff = spm_get('Files',[ cwd,'FunImgRAF/',subExpID(sub).name,'/'],'mean*.img') %mean
conCat_fs=[]; %set an empty matrix to contain all functional images
for ses=1:nses
dir=[cwd,'FunImgRAF/',subExpID(sub).name,'/']; %the location of motion correction file
f=spm_get('Files',dir,'raf*.img') %motion correted files
fs=cellstr(f);
conCat_fs=[conCat_fs;fs]; %concatenate all files
f = []; fs = []; %clear
end
conCat_fs=[conCat_fs;cellstr(ff)]; %normalize mean
jobs{1}.spatial{1}.normalise{1}.write.subj.resample = conCat_fs; %start
jobs{1}.spatial{1}.normalise{1}.write.roptions.bb = [-90 -126 -72
90 90 108]; % bouding box was [-78 -112 -50,78 76 85]. It is suggested that we set it as [-90 -126 -72,90 90 108] or [-78 -112 -70,78 76 85]
jobs{1}.spatial{1}.normalise{1}.write.roptions.vox = [3 3 3]; % set the size of voxel, close to collected
%%%%%%%%%%%%%%% normalization of structual images %%%%%%%%%%%%%%%%%
jobs{1}.spatial{1}.normalise{2}.write.subj.matname = cellstr(sp)
jobs{1}.spatial{1}.normalise{2}.write.subj.resample = cellstr(sm)
jobs{1}.spatial{1}.normalise{2}.write.roptions.vox = [1 1 1]; % set as it is collected
spm_jobman('run',jobs);
clear jobs;
diroffile=[cwd,'FunImgRAF/',subExpID(sub).name,'/'] %add / in the end
files=fullfile(diroffile,'wraf*')
diroffile2=[cwd,'FunImgWRAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy files
cd(diroffile)
delete 'wraf*'
end %end of switch
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%% smoothing %%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if smoothing
dirn=[cwd,'FunImgWRAF/',subExpID(sub).name,'/']; %location of motion corrected/normalized files
fn=spm_get('Files',dirn,'wraf*.img') %motion corrected/normalized files
jobs{1}.spatial{1}.smooth.data = cellstr(fn); %smooth
jobs{1}.spatial{1}.smooth.fwhm=[8 8 8]; % 平滑核大小，可以随意设置。default is 8
spm_jobman('run',jobs);
clear jobs;
diroffile=[cwd,'FunImgWRAF/',subExpID(sub).name,'/'] % add / int the end
files=fullfile(diroffile,'swraf*')
diroffile2=[cwd,'FunImgSWRAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy
cd(diroffile)
delete 'swraf*'
%%%%%%%%%%%%%copy motion correction files to the last step %%%%%%%%%%%%%%%%
diroffile=[cwd,'FunImgRAF/',subExpID(sub).name,'/'] %add / in the end
files=fullfile(diroffile,'rp*.txt')
diroffile2=[cwd,'FunImgSWRAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy
end %end of switch
%以下是使用DARTEL来进行标准化，这一步骤应该和DPARSF的相关功能类似。如果使用这一步，前面的转化，配准，分割，标准化，平滑就不用做了。但需要注意的是，这个过程耗时非常长。每个被试的DARTEL分析可能在1个小时左右。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% DARTEL normalization and smoothing %%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if DARTEL_NormSmooth
%%%%%%%%%%%%%%% converting %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
dirStruc=[cwd,'T1Raw/',subExpID(sub).name,'/']; %location of raw DICOM
cd([ cwd,'DARTELT1Img/',subExpID(sub).name,'/']); %location to export the Analyze.为了方面看结果，把DARTEL的结果都输出到一个单独的文件夹DARTELT1Img中，这里做转化结构像。最前面的转化结构像就不用做了，只转化功能像就行。
ds=spm_get('Files',dirStruc,'*.ima') %list all DICOM file names
hdrs=spm_dicom_headers(ds); %read DICOM header
spm_dicom_convert(hdrs,'all','flat','img'); % convert
display(sprintf('Anatomical run has been finished.')); % show when finished
clear dir;
imgfile=dir ('*.img');
hdrfile=dir ('*.hdr');
movefile(imgfile(1).name,[subExpID(sub).name,'.img']) %change name
movefile(hdrfile(1).name,[subExpID(sub).name,'.hdr']) %change name
%%%%%%%%%%%%%%% coregistration %%%%%%%%%%%%%%%%%%%%%%%%%%%%
s=spm_get('Files',[cwd,'DARTELT1Img/',subExpID(sub).name,'/'],'*.img'); % structural images from DICOM
m=spm_get('Files',[cwd,'FunImgRAF/',subExpID(sub).name,'/'],'mean*.img'); %mean
jobs{1}.spatial{1}.coreg{1}.estimate.ref = cellstr(m); %set mean as the reference
jobs{1}.spatial{1}.coreg{1}.estimate.source = cellstr(s); % structual image is coregisted to mean. mean generated from realignment remains static
spm_jobman('run',jobs);.
clear jobs;
%%%%%%%%%%%%%%%%%% new segmentation %%%%%%%%%%%%%%%%%%%%%%%%
s=spm_get('Files',[cwd,'DARTELT1Img/',subExpID(sub).name,'/'],'*.img'); % structural images from DICOM
matlabbatch{1}.spm.tools.preproc8.channel.vols = cellstr(s);
matlabbatch{1}.spm.tools.preproc8.channel.biasreg = 0.0001;
matlabbatch{1}.spm.tools.preproc8.channel.biasfwhm = 60;
matlabbatch{1}.spm.tools.preproc8.channel.write = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(1).tpm = {'/mnt/nfs/proj/addiction/spm8/toolbox/Seg/TPM.nii,1'};
matlabbatch{1}.spm.tools.preproc8.tissue(1).ngaus = 2;
matlabbatch{1}.spm.tools.preproc8.tissue(1).native = [1 1];
matlabbatch{1}.spm.tools.preproc8.tissue(1).warped = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(2).tpm = {'/mnt/nfs/proj/addiction/spm8/toolbox/Seg/TPM.nii,2'};
matlabbatch{1}.spm.tools.preproc8.tissue(2).ngaus = 2;
matlabbatch{1}.spm.tools.preproc8.tissue(2).native = [1 1];
matlabbatch{1}.spm.tools.preproc8.tissue(2).warped = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(3).tpm = {'/mnt/nfs/proj/addiction/spm8/toolbox/Seg/TPM.nii,3'};
matlabbatch{1}.spm.tools.preproc8.tissue(3).ngaus = 2;
matlabbatch{1}.spm.tools.preproc8.tissue(3).native = [1 0];
matlabbatch{1}.spm.tools.preproc8.tissue(3).warped = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(4).tpm = {'/mnt/nfs/proj/addiction/spm8/toolbox/Seg/TPM.nii,4'};
matlabbatch{1}.spm.tools.preproc8.tissue(4).ngaus = 3;
matlabbatch{1}.spm.tools.preproc8.tissue(4).native = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(4).warped = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(5).tpm = {'/mnt/nfs/proj/addiction/spm8/toolbox/Seg/TPM.nii,5'};
matlabbatch{1}.spm.tools.preproc8.tissue(5).ngaus = 4;
matlabbatch{1}.spm.tools.preproc8.tissue(5).native = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(5).warped = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(6).tpm = {'/mnt/nfs/proj/addiction/spm8/toolbox/Seg/TPM.nii,6'};
matlabbatch{1}.spm.tools.preproc8.tissue(6).ngaus = 2;
matlabbatch{1}.spm.tools.preproc8.tissue(6).native = [0 0];
matlabbatch{1}.spm.tools.preproc8.tissue(6).warped = [0 0];
matlabbatch{1}.spm.tools.preproc8.warp.mrf = 0;
matlabbatch{1}.spm.tools.preproc8.warp.reg = 4;
matlabbatch{1}.spm.tools.preproc8.warp.affreg = 'mni';
matlabbatch{1}.spm.tools.preproc8.warp.samp = 3;
matlabbatch{1}.spm.tools.preproc8.warp.write = [0 0];
spm_jobman('run',matlabbatch)
clear matlabbatch;
%%%%%%%%%%%%%%%%%%vgeneration of templates %%%%%%%%%%%%%%%%%%%%%%%%%
rc1=spm_get('Files',[cwd,'DARTELT1Img/',subExpID(sub).name,'/'],'rc1*.nii');
rc2=spm_get('Files',[cwd,'DARTELT1Img/',subExpID(sub).name,'/'],'rc2*.nii');
matlabbatch{1}.spm.tools.dartel.warp.images = {cellstr(rc1),cellstr(rc2)};
matlabbatch{1}.spm.tools.dartel.warp.settings.template = 'Template';
matlabbatch{1}.spm.tools.dartel.warp.settings.rform = 0;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(1).its = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(1).rparam = [4 2 1e-06];
matlabbatch{1}.spm.tools.dartel.warp.settings.param(1).K = 0;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(1).slam = 16;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(2).its = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(2).rparam = [2 1 1e-06];
matlabbatch{1}.spm.tools.dartel.warp.settings.param(2).K = 0;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(2).slam = 8;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(3).its = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(3).rparam = [1 0.5 1e-06];
matlabbatch{1}.spm.tools.dartel.warp.settings.param(3).K = 1;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(3).slam = 4;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(4).its = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(4).rparam = [0.5 0.25 1e-06];
matlabbatch{1}.spm.tools.dartel.warp.settings.param(4).K = 2;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(4).slam = 2;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(5).its = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(5).rparam = [0.25 0.125 1e-06];
matlabbatch{1}.spm.tools.dartel.warp.settings.param(5).K = 4;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(5).slam = 1;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(6).its = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(6).rparam = [0.25 0.125 1e-06];
matlabbatch{1}.spm.tools.dartel.warp.settings.param(6).K = 6;
matlabbatch{1}.spm.tools.dartel.warp.settings.param(6).slam = 0.5;
matlabbatch{1}.spm.tools.dartel.warp.settings.optim.lmreg = 0.01;
matlabbatch{1}.spm.tools.dartel.warp.settings.optim.cyc = 3;
matlabbatch{1}.spm.tools.dartel.warp.settings.optim.its = 3;
spm_jobman('run',matlabbatch)
clear matlabbatch;
%%%%%%%%% normalization and smoothing 使用DARTEL模板进行标准化%%%%%%%%%%%%%%%%%
conCat_fs=[]; %set an empty matrix to contain all functional images
for ses=1:nses
dir=[cwd,'FunImgRAF/',subExpID(sub).name,'/']; %the location of motion corrected file
f=spm_get('Files',dir,'raf*.img') %motion correted files
fs=cellstr(f);
conCat_fs=[conCat_fs;fs]; %concatenate all files
f = []; fs = []; %clear
end
flowfile=spm_get('Files',[cwd,'DARTELT1Img/',subExpID(sub).name,'/'],'u_rc1*.nii');
Templatefile=spm_get('Files',[cwd,'DARTELT1Img/',subExpID(sub).name,'/'],'Template_6.nii');
matlabbatch{1}.spm.tools.dartel.mni_norm.template =cellstr(Templatefile);
matlabbatch{1}.spm.tools.dartel.mni_norm.data.subj.flowfield =cellstr(flowfile);
matlabbatch{1}.spm.tools.dartel.mni_norm.data.subj.images =conCat_fs;
matlabbatch{1}.spm.tools.dartel.mni_norm.vox = [3 3 3];
matlabbatch{1}.spm.tools.dartel.mni_norm.bb = [-90 -126 -72
90 90 108];
matlabbatch{1}.spm.tools.dartel.mni_norm.preserve = 0;
matlabbatch{1}.spm.tools.dartel.mni_norm.fwhm = [8 8 8];
spm_jobman('run',matlabbatch)
diroffile=[cwd,'FunImgRAF/',subExpID(sub).name,'/'] % ad d / int the end
files=fullfile(diroffile,'s*')
diroffile2=[cwd,'DARTEL_FunImgSWRAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy
cd(diroffile)
delete 'swraf*'
clear matlabbatch;
%%%%%%%%%%%%%copy motion correction files to the last step %%%%%%%%%%%%%%%%
diroffile=[cwd,'FunImgRAF/',subExpID(sub).name,'/'] %add / in the end
files=fullfile(diroffile,'rp*.txt')
diroffile2=[cwd,'DARTEL_FunImgSWRAF/',subExpID(sub).name,'/']
copyfile(files,diroffile2) %copy
end % end of switch
end % end of subLast updated