I see, thanks again :).

David

2016-07-15 13:05 GMT+02:00 Glasser, Matthew <[email protected]>:

> You can, or you can compute on individual rows and average as Steve
> suggested.  It depends on what you are doing with the data where one or
> another is preferred.
>
> Matt.
>
> From: David Hofmann <[email protected]>
> Date: Friday, July 15, 2016 at 3:52 AM
>
> To: Matt Glasser <[email protected]>
> Cc: Stephen Smith <[email protected]>, "Dierker, Donna" <
> [email protected]>, hcp-users <[email protected]>
> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state data
> - 2400 data points instead of 1200 ?
>
> Hi Matthew,
>
> one last clarification: After doing this for LR and RL seperately, I can
> (or have to!) concatenate them together, is this correct?
>
> Thanks so much for the support :)
>
> David
>
> 2016-07-15 4:50 GMT+02:00 Glasser, Matthew <[email protected]>:
>
>> That’s fine, I usually have time along rows for better or for worse…
>>
>> Peace,
>>
>> Matt.
>>
>> From: David Hofmann <[email protected]>
>> Date: Thursday, July 14, 2016 at 12:14 PM
>>
>> To: Matt Glasser <[email protected]>
>> Cc: Stephen Smith <[email protected]>, "Dierker, Donna" <
>> [email protected]>, hcp-users <[email protected]>
>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state data
>> - 2400 data points instead of 1200 ?
>>
>> Hi Matthew,
>>
>> I'm sorry I made a mistake. I meant that I calculated the column mean and
>> subtracted it from each column. For example given a 3 by 2 matrix with 3
>> time points and 2 ROIs
>>
>> Time | ROI 1 | ROI 2
>>   1         3          4
>>   2         2          2
>>   3         1          3
>> ------------------------
>>  mean  2          3
>>
>> Substracting 2 from ROI 1 and 3 from ROI 2 gives me
>>
>> Time | ROI 1 | ROI 2
>>   1         1          1
>>   2         0          -1
>>   3         -1         0
>>
>> hope this clarifies it and this is what you meant. Sorry again for this
>> mistake!
>>
>> David
>>
>>
>> 2016-07-13 22:53 GMT+02:00 Glasser, Matthew <[email protected]>:
>>
>>> 2) Did you subtract the row mean from each row?
>>>
>>> Peace,
>>>
>>> Matt.
>>>
>>> From: David Hofmann <[email protected]>
>>> Date: Wednesday, July 13, 2016 at 9:56 AM
>>>
>>> To: Matt Glasser <[email protected]>
>>> Cc: Stephen Smith <[email protected]>, "Dierker, Donna" <
>>> [email protected]>, hcp-users <[email protected]>
>>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state
>>> data - 2400 data points instead of 1200 ?
>>>
>>> Hi Matthew,
>>>
>>> thank you for the help!
>>>
>>> I did the following:
>>>
>>> 1. I used the "clean" datasets now and extracted my ROI data from the LR
>>> and RL phase encodings (first two sessions)
>>> 2. I calculated the mean across time for every ROI and substracted it,
>>> i.e. I have a 1200 by 112 matrix and calculated the row mean (over time)
>>> and substracted it from each column (ROIs).
>>> 3. I did this for LR and RL seperately and then concatenated them
>>> together
>>>
>>> Can you confirm that this is the correct?
>>>
>>> thanks again!
>>>
>>> David
>>>
>>> 2016-07-13 0:55 GMT+02:00 Glasser, Matthew <[email protected]>:
>>>
>>>> I would recommend using the data with _hp2000_clean in the name.  I a
>>>> referring to taking the mean across time at each point in space and
>>>> subtracting that from the data.
>>>>
>>>> Peace,
>>>>
>>>> Matt.
>>>>
>>>> From: David Hofmann <[email protected]>
>>>> Date: Tuesday, July 12, 2016 at 6:56 AM
>>>> To: Matt Glasser <[email protected]>
>>>> Cc: Stephen Smith <[email protected]>, "Dierker, Donna" <
>>>> [email protected]>, hcp-users <[email protected]>
>>>>
>>>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state
>>>> data - 2400 data points instead of 1200 ?
>>>>
>>>> Hi all,
>>>>
>>>> Regarding Stephen's answer:  I thought it is necessary to concatenate
>>>> the LR/RL phase encoding directions together somehow or can I just treat
>>>> every run seperately? What I basically want is the timecourse from a voxel
>>>> or a region (from preprocessed data) which I can use for further analysis.
>>>>
>>>> Regarding Matthew's answer: I'm afraid I'm not exactly sure what you
>>>> mean by cleaning or removing the mean image from the data. Mean centering?
>>>>
>>>> I used the preprocessed datasets:
>>>>
>>>>
>>>>
>>>> *subjectcode_3T_rfMRI_REST1_preproc.zip *
>>>> \MNINonLinear\Results\rfMRI_REST1_LR
>>>> \MNINonLinear\Results\rfMRI_REST1_RL
>>>>
>>>> Is this the correct data or is it necessary to use some different
>>>> datasets for my specific purposes? (Normally I'd use the netmats datasets,
>>>> but in I'm especially interested in the amygdala which I'm trying to
>>>> extract from the Harvard-Oxford Atlas ROI).
>>>>
>>>> Thanks for your answers!
>>>>
>>>> David
>>>>
>>>> 2016-07-12 12:47 GMT+02:00 Glasser, Matthew <[email protected]>:
>>>>
>>>>> Also it appears you haven’t either cleaned or removed the mean image
>>>>> from the data.
>>>>>
>>>>> Matt.
>>>>>
>>>>> From: <[email protected]> on behalf of Stephen
>>>>> Smith <[email protected]>
>>>>> Date: Tuesday, July 12, 2016 at 3:48 AM
>>>>> To: David Hofmann <[email protected]>
>>>>> Cc: "Dierker, Donna" <[email protected]>, hcp-users <
>>>>> [email protected]>
>>>>>
>>>>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state
>>>>> data - 2400 data points instead of 1200 ?
>>>>>
>>>>> Hi - no we do not (in general for resting-state) ever recommend
>>>>> temporal contatenation like this before further analyses - for the reason
>>>>> you're seeing here.
>>>>> For example, for the HCP released netmats, we take the 4 runs, one at
>>>>> a time, estimate the 4 (zstat) netmats, and average those.
>>>>> Cheers.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> On 12 Jul 2016, at 09:43, David Hofmann <[email protected]>
>>>>> wrote:
>>>>>
>>>>> Hi Michael,
>>>>>
>>>>> thanks for the reply, using a different routine works and shows 1200
>>>>> volumes. But now it seems that in some data (extracted ROI mean) there is 
>>>>> a
>>>>> huge difference between LR and RL phase encoding in the signal (see
>>>>> attached picture). Is this "normal" and can I just concatenate LR and RL
>>>>> together or is this not possible?
>>>>>
>>>>> greetings
>>>>>
>>>>> David
>>>>>
>>>>> 2016-07-11 19:43 GMT+02:00 Harms, Michael <[email protected]>:
>>>>>
>>>>>>
>>>>>> Hi,
>>>>>> Can you check the number of volumes/frames of the unpacked
>>>>>> REST1_{LR,RL}.nii.gz files using something other than your Matlab/SPM
>>>>>> tools?  e.g., FSL’s ‘fslhd’ or ‘fslnvols’ commands.
>>>>>>
>>>>>> cheers,
>>>>>> -MH
>>>>>>
>>>>>> --
>>>>>> Michael Harms, Ph.D.
>>>>>> -----------------------------------------------------------
>>>>>> Conte Center for the Neuroscience of Mental Disorders
>>>>>> Washington University School of Medicine
>>>>>> Department of Psychiatry, Box 8134
>>>>>> 660 South Euclid Ave. Tel: 314-747-6173
>>>>>> St. Louis, MO  63110 Email: [email protected]
>>>>>>
>>>>>> From: <[email protected]> on behalf of David
>>>>>> Hofmann <[email protected]>
>>>>>> Date: Monday, July 11, 2016 at 3:15 AM
>>>>>> To: "Dierker, Donna" <[email protected]>
>>>>>> Cc: hcp-users <[email protected]>
>>>>>> Subject: Re: [HCP-Users] Extracting ROI data from HCP resting state
>>>>>> data - 2400 data points instead of 1200 ?
>>>>>>
>>>>>> Hi Donna and others,
>>>>>>
>>>>>> thanks for your answer. I'm facing a difficulty with extracting data
>>>>>> from the preprocessed files, that is they seems to each contain 2400 data
>>>>>> points rather than 1200 like described in the documentation.
>>>>>>
>>>>>> I downloaded the 10 subjects data set and used the following files: 
>>>>>> *subjectcode_3T_rfMRI_REST1_preproc.zip,
>>>>>> *from which I assume that these are the preprocessed files.
>>>>>>
>>>>>> It contains two datasets LR and RL:
>>>>>>
>>>>>> \MNINonLinear\Results\rfMRI_REST1_LR
>>>>>> \MNINonLinear\Results\rfMRI_REST1_RL
>>>>>>
>>>>>> I unpacked these files:
>>>>>>
>>>>>> rfMRI_REST1_LR.nii.gz
>>>>>> rfMRI_REST1_RL.nii.gz
>>>>>>
>>>>>> and read them as 4D NIFTI with Matlab and an SPM function. Afterwards
>>>>>> they each contain 2400 data points (dimension: 91 109 91 2400), but in 
>>>>>> the
>>>>>> documention it says they each should contain only 1200 data points. So 
>>>>>> I'm
>>>>>> not sure if I did something wrong.
>>>>>>
>>>>>> greetings
>>>>>>
>>>>>> David
>>>>>>
>>>>>>
>>>>>> 2016-06-30 18:30 GMT+02:00 Dierker, Donna <[email protected]>:
>>>>>>
>>>>>>> Hi David,
>>>>>>>
>>>>>>> I hope this publication answers your questions about HCP rfMRI
>>>>>>> preprocessing:
>>>>>>>
>>>>>>> Resting-state fMRI in the Human Connectome Project.
>>>>>>> Smith SM1, Beckmann CF, Andersson J, Auerbach EJ, Bijsterbosch J,
>>>>>>> Douaud G, Duff E, Feinberg DA, Griffanti L, Harms MP, Kelly M, Laumann 
>>>>>>> T,
>>>>>>> Miller KL, Moeller S, Petersen S, Power J, Salimi-Khorshidi G, Snyder 
>>>>>>> AZ,
>>>>>>> Vu AT, Woolrich MW, Xu J, Yacoub E, Uğurbil K, Van Essen DC, Glasser MF;
>>>>>>> WU-Minn HCP Consortium.
>>>>>>> http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720828/
>>>>>>>
>>>>>>> I am only used to seeing what it is in the fix extended packages, so
>>>>>>> I'm not sure all these volumes are in the basic fix packages, but here 
>>>>>>> are
>>>>>>> NIFTI volumes in a sample subject's rfMRI subdirectories:
>>>>>>>
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000_clean.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000.ica/filtered_func_data.ica/mask.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_LR/rfMRI_REST1_LR.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000_clean.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000.ica/filtered_func_data.ica/mask.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST1_RL/rfMRI_REST1_RL.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000_clean.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000.ica/filtered_func_data.ica/mask.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_LR/rfMRI_REST2_LR.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000_clean.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000.ica/filtered_func_data.ica/mask.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000.ica/filtered_func_data.ica/melodic_IC.nii.gz
>>>>>>>
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL_hp2000.ica/filtered_func_data.ica/melodic_oIC.nii.gz
>>>>>>> 177645/MNINonLinear/Results/rfMRI_REST2_RL/rfMRI_REST2_RL.nii.gz
>>>>>>>
>>>>>>> Maybe this page will help explain those:
>>>>>>>
>>>>>>>
>>>>>>> http://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/rfMRIconnectivity/
>>>>>>>
>>>>>>> But keep in mind that for neocortex, you can take advantage of the
>>>>>>> surface data the HCP provides (e.g., fsaverage_32k/*surf.gii, 
>>>>>>> *dscalar.nii
>>>>>>> and *dtseries.nii).  You can get better inter-subject
>>>>>>> registration/alignment on the surface, if that will be a factor in your
>>>>>>> study.
>>>>>>>
>>>>>>> Donna
>>>>>>>
>>>>>>>
>>>>>>> On Jun 28, 2016, at 6:30 PM, David Hofmann <[email protected]>
>>>>>>> wrote:
>>>>>>>
>>>>>>> > Hi all,
>>>>>>> >
>>>>>>> > I would like to extract ROI data (only neocortex) 'manually' e.g.
>>>>>>> using a ROI from Harvard-Oxford atlas from HCP resting state data, but 
>>>>>>> I'm
>>>>>>> not sure which (nifti) files to use and where to find them. I'm also
>>>>>>> looking for some information about the preprocessing steps applied to 
>>>>>>> the
>>>>>>> resting state data that is, if some additional steps (e.g. filtering) 
>>>>>>> have
>>>>>>> to be carried out before ROI extraction or if this has already been 
>>>>>>> done.
>>>>>>> >
>>>>>>> > Any help on this appreciated!
>>>>>>> >
>>>>>>> > Thanks
>>>>>>> >
>>>>>>> > David
>>>>>>> > _______________________________________________
>>>>>>> > HCP-Users mailing list
>>>>>>> > [email protected]
>>>>>>> > http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>>>>>> >
>>>>>>>
>>>>>>>
>>>>>> _______________________________________________
>>>>>> HCP-Users mailing list
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>>>>>>
>>>>>>
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>>>>>
>>>>>
>>>>> _______________________________________________
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>>>>> <timecourse.png>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> ---------------------------------------------------------------------------
>>>>> Stephen M. Smith, Professor of Biomedical Engineering
>>>>> Head of Analysis,  Oxford University FMRIB Centre
>>>>>
>>>>> FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
>>>>> +44 (0) 1865 222726  (fax 222717)
>>>>> [email protected]    http://www.fmrib.ox.ac.uk/~steve
>>>>>
>>>>> ---------------------------------------------------------------------------
>>>>>
>>>>> Stop the cultural destruction of Tibet <http://smithinks.net>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> _______________________________________________
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>
>
>
> --
> David Hofmann (M.Sc.)
> Institut für Medizinische Psychologie und Systemneurowissenschaften
> Von-Esmarch-Strasse 52
> 48149 Münster
> Tel: 0251/ 8352794
> Mobil: 0152/ 09822352
> Email: [email protected]
>
> Institute of Medical Psychology and Systems Neuroscience
> University of Muenster
> Von-Esmarch-Str. 52
> D-48149 Muenster, Germany
> Phone: +49 (0) 251 - 83 52794
> Mobile: +49 (0) 152 - 09822352
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>
> http://campus.uni-muenster.de/medpsych.html
>
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-- 
David Hofmann (M.Sc.)
Institut für Medizinische Psychologie und Systemneurowissenschaften
Von-Esmarch-Strasse 52
48149 Münster
Tel: 0251/ 8352794
Mobil: 0152/ 09822352
Email: [email protected]

Institute of Medical Psychology and Systems Neuroscience
University of Muenster
Von-Esmarch-Str. 52
D-48149 Muenster, Germany
Phone: +49 (0) 251 - 83 52794
Mobile: +49 (0) 152 - 09822352
E-Mail: [email protected]

http://campus.uni-muenster.de/medpsych.html

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