[HCP-Users] MATLAB libraries in Resting State Stats script
Hello all, I've been working with the resting state stats batch script, and it seems to be running correctly on our data. I have it set to use the compiled "MCR" version of the RestingStateStats matlab script. However, I'd like to make a couple modifications to that script, most notably to save out some data files that are not currently set to save to file. When I modify the matlab version of the script and then set the shell script to use normal matlab instead of MCR, I get errors that functions normalise and rms are not defined. I was wondering if anyone knows where these functions are defined (or what library path I'd need to add in the matlab script). I'm hesitant to simply write my own versions of those functions since I don't want to assume I know exactly how they're normalizing/computing root mean square. Any help would be appreciated. Thanks, Andrew Poppe, Ph.D. Postdoctoral Researcher Olin Neuropsychiatry Research Center Institute of Living Hartford Hospital ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] Bias Field setting in Resting State Stats script
Okay great, that was my understanding. Just wanted to make sure I wasn't missing something. Thanks! Andrew On Thu, Sep 6, 2018 at 9:54 AM Glasser, Matthew wrote: > In that case I believe you want “NONE” because you don’t need to mess with > it—it was already done correctly. > > Matt. > > From: Andrew Poppe > Date: Thursday, September 6, 2018 at 9:49 PM > To: Matt Glasser > Cc: "hcp-users@humanconnectome.org" > Subject: Re: [HCP-Users] Bias Field setting in Resting State Stats script > > We used "SEBASED" for the bias correction setting in the fmri volume step. > > Andrew > > On Tue, Sep 4, 2018 at 5:40 PM Glasser, Matthew > wrote: > >> What setting did you use in fMRIVolume? >> >> Matt. >> >> From: on behalf of Andrew Poppe < >> poppe...@gmail.com> >> Date: Wednesday, September 5, 2018 at 4:35 AM >> To: "hcp-users@humanconnectome.org" >> Subject: [HCP-Users] Bias Field setting in Resting State Stats script >> >> Hello all, >> >> I'm working on running the resting state stats batch script on our own >> data, and I am a bit stuck on what to set the bias field setting to. Based >> on the comments in the code as well as the code itself I think I have a >> general idea of what it's doing, but I wanted to specifically ask since I'm >> not 100% on what the setting should be. Could you briefly explain what the >> options represent? >> >> Thanks a lot! >> >> Andrew Poppe, Ph.D. >> Postdoctoral Researcher >> Olin Neuropsychiatry Research Center >> Institute of Living >> Hartford Hospital >> >> ___ >> HCP-Users mailing list >> HCP-Users@humanconnectome.org >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users >> >> >> -- >> >> The materials in this message are private and may contain Protected >> Healthcare Information or other information of a sensitive nature. If you >> are not the intended recipient, be advised that any unauthorized use, >> disclosure, copying or the taking of any action in reliance on the contents >> of this information is strictly prohibited. If you have received this email >> in error, please immediately notify the sender via telephone or return mail. >> > > -- > > The materials in this message are private and may contain Protected > Healthcare Information or other information of a sensitive nature. If you > are not the intended recipient, be advised that any unauthorized use, > disclosure, copying or the taking of any action in reliance on the contents > of this information is strictly prohibited. If you have received this email > in error, please immediately notify the sender via telephone or return mail. > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] Bias Field setting in Resting State Stats script
We used "SEBASED" for the bias correction setting in the fmri volume step. Andrew On Tue, Sep 4, 2018 at 5:40 PM Glasser, Matthew wrote: > What setting did you use in fMRIVolume? > > Matt. > > From: on behalf of Andrew Poppe < > poppe...@gmail.com> > Date: Wednesday, September 5, 2018 at 4:35 AM > To: "hcp-users@humanconnectome.org" > Subject: [HCP-Users] Bias Field setting in Resting State Stats script > > Hello all, > > I'm working on running the resting state stats batch script on our own > data, and I am a bit stuck on what to set the bias field setting to. Based > on the comments in the code as well as the code itself I think I have a > general idea of what it's doing, but I wanted to specifically ask since I'm > not 100% on what the setting should be. Could you briefly explain what the > options represent? > > Thanks a lot! > > Andrew Poppe, Ph.D. > Postdoctoral Researcher > Olin Neuropsychiatry Research Center > Institute of Living > Hartford Hospital > > ___ > HCP-Users mailing list > HCP-Users@humanconnectome.org > http://lists.humanconnectome.org/mailman/listinfo/hcp-users > > > -- > > The materials in this message are private and may contain Protected > Healthcare Information or other information of a sensitive nature. If you > are not the intended recipient, be advised that any unauthorized use, > disclosure, copying or the taking of any action in reliance on the contents > of this information is strictly prohibited. If you have received this email > in error, please immediately notify the sender via telephone or return mail. > ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
[HCP-Users] Bias Field setting in Resting State Stats script
Hello all, I'm working on running the resting state stats batch script on our own data, and I am a bit stuck on what to set the bias field setting to. Based on the comments in the code as well as the code itself I think I have a general idea of what it's doing, but I wanted to specifically ask since I'm not 100% on what the setting should be. Could you briefly explain what the options represent? Thanks a lot! Andrew Poppe, Ph.D. Postdoctoral Researcher Olin Neuropsychiatry Research Center Institute of Living Hartford Hospital ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
Re: [HCP-Users] Problem using FIX clean data in parcellated stats pipeline
Would the following commands accomplish adding the mean of the non-clean
data to each volume of the FIX cleaned data?
Original.dtseries.nii : non-cleaned dense data
Clean.dtseries.nii: cleaned data
wb_command -cifti-reduce Original.dtseries.nii MEAN MEAN.dscalar.nii
wb_command -cifti-math "a+b" clean_plus_mean.dtseries.nii -var a
Clean.dtseries.nii -var b MEAN.dscalar.nii -select 1 1 -repeat
Is this correct? Is there a better way to do it?
Thanks,
Andrew Poppe, Ph.D.
Postdoctoral Fellow
Olin Neuropsychiatry Research Center
Institute of Living
Hartford Hospital
On Fri, Jan 27, 2017 at 4:03 PM, Glasser, Matthew <glass...@wustl.edu>
wrote:
> Right. That is decently long for task fMRI runs. We think that with
> short runs it may be hard to get optimal results with ICA+FIX, but we are
> working on solutions for this.
>
> Peace,
>
> Matt.
>
> From: Andrew Poppe <poppe...@umn.edu>
> Date: Friday, January 27, 2017 at 3:00 PM
> To: Matt Glasser <glass...@wustl.edu>
> Cc: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
> Subject: Re: [HCP-Users] Problem using FIX clean data in parcellated
> stats pipeline
>
> Thank you for the quick reply!
>
> So you would recommend adding the mean image for both dense and
> parcellated analyses? Our task runs are 718 volumes each with a TR of 0.72
> seconds.
>
> Thanks again,
>
>
> Andrew Poppe, Ph.D.
> Postdoctoral Fellow
> Olin Neuropsychiatry Research Center
> Institute of Living
> Hartford Hospital
>
> On Fri, Jan 27, 2017 at 3:00 PM, Glasser, Matthew <glass...@wustl.edu>
> wrote:
>
>> It is correct that the taskfMRI pipeline requires the data to not be
>> demeaned and by default currently the ICA+FIX pipeline produces demeaned
>> data with recent versions of FSL because the mean is removed by the
>> highpass filter. It would be sufficient to compute the mean image from the
>> uncleaned data and add it to the cleaned data. If there are any other bugs
>> in the taskfMRI Pipeline that interact with ICA+FIX cleaned data, I will
>> know about them soon as I am doing similar processing. How long are your
>> task fMRI runs?
>>
>> Peace,
>>
>> Matt.
>>
>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Andrew Poppe <
>> poppe...@umn.edu>
>> Date: Friday, January 27, 2017 at 12:58 PM
>> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
>> Subject: [HCP-Users] Problem using FIX clean data in parcellated stats
>> pipeline
>>
>> Howdy HCP folks,
>>
>> We've recently run into a problem when attempting to use ICA+FIX cleaned
>> data in a parcellated stats analysis pipeline. I'll run through what we've
>> done, what happened, and what I think is going wrong. Hopefully you can
>> provide some insight into if we've done things correctly and if so, what to
>> do about it.
>>
>> We are using the IcaFixProcessingBatch.sh script to apply ICA+FIX to our
>> data using the provided HCP_hp2000.RData training data, following the
>> application of GenericfMRIVolumeProcessingPipelineBatch.sh and
>> GenericfMRISurfaceProcessingPipelineBatch.sh.
>>
>> This produces a file with a name ending in _Atlas_hp2000_clean.dtserie
>> s.nii.
>>
>> Previously, before attempting to use ICA+FIX, we have successfully used
>> the TaskfMRIAnalysisBatch.sh script to run a parcellated analysis. In order
>> to use ICA+FIX results as our input data, I changed the name of the clean
>> data to be ${TASK}_Atlas.dtseries.nii to "trick" the batch script to use
>> the cleaned data instead of the original data.
>>
>> This worked fine when doing a dense analysis, but the analysis failed
>> when trying to run a parcellated analysis.
>>
>> Specifically, when examining the logs of the analysis, the output of
>> film_gls included the line: *numTS=0* when using FIX cleaned data when
>> it had been *numTS=360* when using the original data.
>>
>> The film_gls code appears to do some masking of non-brain voxels toward
>> the beginning, and this masking process effectively zeroed out all values
>> in the FIX cleaned data whereas it allowed all values to remain when using
>> original data. Looking at the FAKENIFTI files produced from the original
>> data compared with ICA+FIX cleaned data, it seems the ranges are quite
>> different.
>>
>> For the original data (for a representative subject), the mean value of
>> the FAKENIFTI was around 11000 (range was ~5000 to ~15000). For the FIX
>> cleaned data, the mean was effectively zero (range was -420 t
[HCP-Users] Problem using FIX clean data in parcellated stats pipeline
Howdy HCP folks,
We've recently run into a problem when attempting to use ICA+FIX cleaned
data in a parcellated stats analysis pipeline. I'll run through what we've
done, what happened, and what I think is going wrong. Hopefully you can
provide some insight into if we've done things correctly and if so, what to
do about it.
We are using the IcaFixProcessingBatch.sh script to apply ICA+FIX to our
data using the provided HCP_hp2000.RData training data, following the
application of GenericfMRIVolumeProcessingPipelineBatch.sh and
GenericfMRISurfaceProcessingPipelineBatch.sh.
This produces a file with a name ending
in _Atlas_hp2000_clean.dtseries.nii.
Previously, before attempting to use ICA+FIX, we have successfully used
the TaskfMRIAnalysisBatch.sh script to run a parcellated analysis. In order
to use ICA+FIX results as our input data, I changed the name of the clean
data to be ${TASK}_Atlas.dtseries.nii to "trick" the batch script to use
the cleaned data instead of the original data.
This worked fine when doing a dense analysis, but the analysis failed when
trying to run a parcellated analysis.
Specifically, when examining the logs of the analysis, the output of
film_gls included the line: *numTS=0* when using FIX cleaned data when it
had been *numTS=360* when using the original data.
The film_gls code appears to do some masking of non-brain voxels toward the
beginning, and this masking process effectively zeroed out all values in
the FIX cleaned data whereas it allowed all values to remain when using
original data. Looking at the FAKENIFTI files produced from the original
data compared with ICA+FIX cleaned data, it seems the ranges are quite
different.
For the original data (for a representative subject), the mean value of the
FAKENIFTI was around 11000 (range was ~5000 to ~15000). For the FIX cleaned
data, the mean was effectively zero (range was -420 to 382).
During the masking procedure in film_gls, a "mask" is produced by averaging
voxel values across time. Next, that mask is binarized based on a
user-supplied threshold value. The default threshold value supplied to
film_gls in the TaskfMRIAnalysis pipeline scripts is 1. In the case of the
original data, all values in the mask are set to 1 since the range of this
mean mask volume is 6346.99 to 14440.96. However, for the mean mask created
from the FIX cleaned data, the range is -2.638159e-06 to 1.118895e-06,
such that binarizing with a threshold of 1 sets all values to 0.
If I understand this correctly, it seems that this masking procedure within
film_gls is unnecessary during a parcellated analysis, because we already
know that there are no "non-brain" values to get rid of. So, I have a
couple questions about this:
1) Do the values for the ICA+FIX cleaned data I presented seem
representative of FIX results in your experience? Meaning, instead of a
mean around 1 the data have a zero mean with a greatly reduced range.
Also, when taking an average across time, is it common to see effectively
zero values for all parcels?
2) If the answer to #1 is "yes," would it be okay to circumvent this
masking process within film_gls? I could imagine altering the pipeline
script to instead of providing a 1 for the threshold, provide the minimum
voxel value in the FAKENIFTI instead, insuring that the binarizing
procedure created a mask of all 1s.
Any help or insight would be greatly appreciated, and please let me know if
you need more information. The relevant parts of the film_gls.cc code are:
read_volume4D(input_data,globalopts.inputDataName.value());
reference=input_data[int(input_data.tsize()/2)-1];
copybasicproperties(input_data,reference);
mask=meanvol(input_data);
variance=variancevol(input_data);
input_data-=mask;
mask.binarise(globalopts.thresh.value(),mask.max()+1,exclusive);
variance.binarise(1e-10,variance.max()+1,exclusive); //variance mask
needed if thresh is -ve to remove background voxels (0 variance)
mask*=variance; //convolved mask ensures that only super-threshold
non-background voxels pass
datam=input_data.matrix(mask,labels);
And the relevant call to film_gls comes in TaskfMRILevel1.v2.0.sh on line
235:
film_gls --rn=${FEATDir}/ParcellatedStats
--in=${FEATDir}/${LevelOnefMRIName}_Atlas"$TemporalFilterString""$SmoothingString"${RegString}${ParcellationString}_FAKENIFTI.nii.gz
--pd="$DesignMatrix" --con=${DesignContrasts} --fcon=${DesignfContrasts}
--thr=1 --mode=volumetric
Cheers,
Andrew Poppe, Ph.D.
Postdoctoral Fellow
Olin Neuropsychiatry Research Center
Institute of Living
Hartford Hospital
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[HCP-Users] Possible Typo in task fmri script
Hello, I was recently adapting some of your great tfMRI analysis pipeline scripts for use with newly collected HCP-compliant data, and I noticed a line that I can't understand. In TaskfMRIAnalysis.v2.0.sh (called by TaskfMRIAnalysis.sh when "new" FSL versions are detected) on line 126 it says: LevelOnefsfNames=`echo $LevelOnefMRINames | sed 's/ /@/g'` I may be misunderstanding something, so I thought I'd ask, but it seems to me that second variable should be $LevelOnefsfNames. Most likely, it won't cause a problem because by default the two variables are set to be identical in the TaskfMRIAnalysisBatch.sh script. Thanks for any input about this line. Thanks, Andrew Poppe, Ph.D. Postdoctoral Researcher Olin Neuropsychiatry Research Center Institute of Living Hartford Hospital ___ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
