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 <glass...@wustl.edu>:
> 2) Did you subtract the row mean from each row?
>
> Peace,
>
> Matt.
>
> From: David Hofmann <davidhofma...@gmail.com>
> Date: Wednesday, July 13, 2016 at 9:56 AM
>
> To: Matt Glasser <glass...@wustl.edu>
> Cc: Stephen Smith <st...@fmrib.ox.ac.uk>, "Dierker, Donna" <
> do...@wustl.edu>, hcp-users <hcp-users@humanconnectome.org>
> 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 <glass...@wustl.edu>:
>
>> 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 <davidhofma...@gmail.com>
>> Date: Tuesday, July 12, 2016 at 6:56 AM
>> To: Matt Glasser <glass...@wustl.edu>
>> Cc: Stephen Smith <st...@fmrib.ox.ac.uk>, "Dierker, Donna" <
>> do...@wustl.edu>, hcp-users <hcp-users@humanconnectome.org>
>>
>> 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 <glass...@wustl.edu>:
>>
>>> Also it appears you haven’t either cleaned or removed the mean image
>>> from the data.
>>>
>>> Matt.
>>>
>>> From: <hcp-users-boun...@humanconnectome.org> on behalf of Stephen
>>> Smith <st...@fmrib.ox.ac.uk>
>>> Date: Tuesday, July 12, 2016 at 3:48 AM
>>> To: David Hofmann <davidhofma...@gmail.com>
>>> Cc: "Dierker, Donna" <do...@wustl.edu>, hcp-users <
>>> hcp-users@humanconnectome.org>
>>>
>>> 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 <davidhofma...@gmail.com> 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 <mha...@wustl.edu>:
>>>
>>>>
>>>> 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: mha...@wustl.edu
>>>>
>>>> From: <hcp-users-boun...@humanconnectome.org> on behalf of David
>>>> Hofmann <davidhofma...@gmail.com>
>>>> Date: Monday, July 11, 2016 at 3:15 AM
>>>> To: "Dierker, Donna" <do...@wustl.edu>
>>>> Cc: hcp-users <hcp-users@humanconnectome.org>
>>>> 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 <do...@wustl.edu>:
>>>>
>>>>> 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 <davidhofma...@gmail.com>
>>>>> 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
>>>>> > HCP-Users@humanconnectome.org
>>>>> > http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>>>> >
>>>>>
>>>>>
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>>> <timecourse.png>
>>>
>>>
>>>
>>>
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>>>
>>> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
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