help > how to do functional preprocessing and denoising only with structural image preprocessed
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Dec 28, 2018  07:12 AM | Jing Jiang
how to do functional preprocessing and denoising only with structural image preprocessed
Dear CONN experts,

I am encountering a "Not ready to process step conn_process_5" problem when doing functional preprocessing and denoising only but cannot find an answer elsewhere.

My experiment involves multiple tasks, and each participant has one functional image for each task and one structural image. To reduce computational time, i did structural image preprocessing first and then planned to use the preprocessed structural image and the same conn*.mat file for further analysis (functional preprocessing and denoising),so that it will use the structural preprocessing. However, after doing all preprocessing, the denoising did pass through, it reports such info (not 'error') as below and no filtered data was generated. I pasted the commands I used as below. Can any expert help to find out a solution?

Thanks a lot in advance!

Jing

Step 1/7: Expanding conditions
100.0% (Condition rest)

Step 2/7: Importing conditions/covariates
100.0% (Subject 1 Session 1)
Step 3/7: Updating Denosing variables
Not ready to process step conn_process_5
saved /media/storage/CausalConnectome/tmsfmri/test/NTHC1003/conn_NTHC1003.mat

------------------------------------------------------------------
##commands for structural preprocessing
cwd=[pwd '/' subid];
batch.filename=fullfile(cwd, ['conn_' subid '.mat']);
%% --------------------------------- CONN Set up ----------------------------------
%% data
STRUCTURAL_FILE={[cwd, '/CausCon_' subid '_t1.nii']};
batch.Setup.structurals=STRUCTURAL_FILE;
%% preprocessing steps
batch.Setup.preprocessing.steps={'structural_center','structural_segment&normalize'};
conn_batch(batch)

## commands for functional preprocessing and denoising
cwd=[pwd '/' subid];
batch.filename=fullfile(cwd, ['conn_' subid '.mat']);
%% --------------------------------- CONN Set up ----------------------------------
batch.Setup.isnew=0; % use the old setting from struct!!!
batch.Setup.overwrite=0; % not overwrite!!!
batch.Setup.RT=2.4;
%% data
FUNCTIONAL_FILE={[cwd, '/func/CausCon_' subid '_tms_' site '.nii.gz']};
batch.Setup.functionals=FUNCTIONAL_FILE;
batch.Setup.outputfiles= [0,1,1,1,1,0]; %Optional output files (outputfiles(1): 1/0 creates confound beta-maps; outputfiles(2): 1/0 creates
% confound-corrected timeseries; outputfiles(3): 1/0 creates seed-to-voxel r-maps) ;outputfiles(4):
% 1/0 creates seed-to-voxel p-maps) ;outputfiles(5): 1/0 creates seed-to-voxel FDR-p-maps);
% outputfiles(6): 1/0 creates ROI-extraction REX files; [0,0,0,0,0,0]

%% preprocessing steps

batch.Setup.preprocessing.steps={'functional_realign&unwarp' ,'functional_center', ...
'functional_normalize_direct','functional_smooth'};
batch.Setup.preprocessing.fwhm=6;
%% --------------------------------- CONN denoising ---------------------------------
batch.Setup.conditions.names={'rest'};
batch.Setup.conditions.onsets{1}{1}{1}=0;
batch.Setup.conditions.durations{1}{1}{1}=inf;
batch.Denoising.filter=[0.008, inf]; % frequency filter (band-pass values, in Hz)
batch.Denoising.confounds.names=... % Effects to be included as confounds (cell array of effect names, effect names can be first-level covariate names, condition names, or noise ROI names)
{'Grey Matter','White Matter','CSF','realignment'};
batch.Denoising.confounds.dimensions=... % dimensionality of each effect listed above (cell array of values, leave empty a particular value to set to the default value -maximum dimensions of the corresponding effect-)
{1, 3, 3, []};
batch.Denoising.confounds.deriv=... % derivatives order of each effect listed above (cell array of values, leave empty a particular value to set to the default value)
{0, 0, 0, 1};
batch.Denoising.overwrite=1; % skip previously-processed subjects
batch.Denoising.done=1; % use default denoising step (CompCor, motion regression, scrubbing, detrending)
end
conn_batch(batch)
Sep 10, 2019  11:09 AM | Ariana Familiar
RE: how to do functional preprocessing and denoising only with structural image preprocessed
Hello,

Did you figure out what the issue was? I'm running into a similar issue, although it gets through importing ROI data and then throws the error.

Ariana