Thank you for the clarification.
Here is a tree structure of one subject folder
"tfMRI_EMOTION_hp200_s2_level2.feat" , could you tell me which cope folder
you are talking about? there is six of them, and which file to be read on
matlab?
.
├── 139435_tfMRI_EMOTION_level2_hp200_s2.dscalar.nii
├── Contrasts.txt
├── design.con
├── design_cov.png
├── design_cov.ppm
├── design.fsf
├── design.grp
├── design.mat
├── design.png
├── design.ppm
└── GrayordinatesStats
├── cope1.feat
│ ├── cope1.dtseries.nii
│ ├── logfile
│ ├── mask.dtseries.nii
│ ├── mean_random_effects_var1.dtseries.nii
│ ├── pe1.dtseries.nii
│ ├── res4d.dtseries.nii
│ ├── tdof_t1.dtseries.nii
│ ├── tstat1.dtseries.nii
│ ├── varcope1.dtseries.nii
│ ├── weights1.dtseries.nii
│ ├── zflame1lowertstat1.dtseries.nii
│ ├── zflame1uppertstat1.dtseries.nii
│ └── zstat1.dtseries.nii
├── cope2.feat
│ ├── cope1.dtseries.nii
│ ├── logfile
│ ├── mask.dtseries.nii
│ ├── mean_random_effects_var1.dtseries.nii
│ ├── pe1.dtseries.nii
│ ├── res4d.dtseries.nii
│ ├── tdof_t1.dtseries.nii
│ ├── tstat1.dtseries.nii
│ ├── varcope1.dtseries.nii
│ ├── weights1.dtseries.nii
│ ├── zflame1lowertstat1.dtseries.nii
│ ├── zflame1uppertstat1.dtseries.nii
│ └── zstat1.dtseries.nii
├── cope3.feat
│ ├── cope1.dtseries.nii
│ ├── logfile
│ ├── mask.dtseries.nii
│ ├── mean_random_effects_var1.dtseries.nii
│ ├── pe1.dtseries.nii
│ ├── res4d.dtseries.nii
│ ├── tdof_t1.dtseries.nii
│ ├── tstat1.dtseries.nii
│ ├── varcope1.dtseries.nii
│ ├── weights1.dtseries.nii
│ ├── zflame1lowertstat1.dtseries.nii
│ ├── zflame1uppertstat1.dtseries.nii
│ └── zstat1.dtseries.nii
├── cope4.feat
│ ├── cope1.dtseries.nii
│ ├── logfile
│ ├── mask.dtseries.nii
│ ├── mean_random_effects_var1.dtseries.nii
│ ├── pe1.dtseries.nii
│ ├── res4d.dtseries.nii
│ ├── tdof_t1.dtseries.nii
│ ├── tstat1.dtseries.nii
│ ├── varcope1.dtseries.nii
│ ├── weights1.dtseries.nii
│ ├── zflame1lowertstat1.dtseries.nii
│ ├── zflame1uppertstat1.dtseries.nii
│ └── zstat1.dtseries.nii
├── cope5.feat
│ ├── cope1.dtseries.nii
│ ├── logfile
│ ├── mask.dtseries.nii
│ ├── mean_random_effects_var1.dtseries.nii
│ ├── pe1.dtseries.nii
│ ├── res4d.dtseries.nii
│ ├── tdof_t1.dtseries.nii
│ ├── tstat1.dtseries.nii
│ ├── varcope1.dtseries.nii
│ ├── weights1.dtseries.nii
│ ├── zflame1lowertstat1.dtseries.nii
│ ├── zflame1uppertstat1.dtseries.nii
│ └── zstat1.dtseries.nii
└── cope6.feat
├── cope1.dtseries.nii
├── logfile
├── mask.dtseries.nii
├── mean_random_effects_var1.dtseries.nii
├── pe1.dtseries.nii
├── res4d.dtseries.nii
├── tdof_t1.dtseries.nii
├── tstat1.dtseries.nii
├── varcope1.dtseries.nii
├── weights1.dtseries.nii
├── zflame1lowertstat1.dtseries.nii
├── zflame1uppertstat1.dtseries.nii
└── zstat1.dtseries.nii
Cheers,
Yassine
Le mar. 27 mars 2018 à 12:18, Harms, Michael <mha...@wustl.edu> a écrit :
>
>
> Certainly that can be done. Take the beta (cope) maps from the CIFTI
> data, load them into (e.g., matlab), and correlate those vectors across
> subjects. If you specifically want only the cortex, you’d need to exclude
> the subcortical voxels from the grayordinates.
>
>
>
> There is no need to go back to voxels for what you are trying to do.
>
>
>
> Cheers,
>
> -MH
>
>
>
> --
>
> Michael Harms, Ph.D.
>
> -----------------------------------------------------------
>
> Associate Professor of Psychiatry
>
> Washington University School of Medicine
>
> Department of Psychiatry, Box 8134
>
> 660 South Euclid Ave
> <https://maps.google.com/?q=660+South+Euclid+Ave&entry=gmail&source=g>.
> Tel: 314-747-6173 <(314)%20747-6173>
>
> St. Louis, MO 63110 Email: mha...@wustl.edu
>
>
>
> *From: *Yassine Benhajali <yanama...@gmail.com>
> *Date: *Tuesday, March 27, 2018 at 11:05 AM
> *To: *"Harms, Michael" <mha...@wustl.edu>
> *Cc: *NEUROSCIENCE tim <tsc...@mst.edu>, hcp-users <
> hcp-users@humanconnectome.org>
>
>
> *Subject: *Re: [HCP-Users] Convert activation cifti data to volume nifti
>
>
>
> Ok, here te hole story behind what I try to achieve:
>
>
>
> - What I did?
>
> The surface maps you see on the figure is originally a volume based
> activation maps that I mapped on surface. This map is generated from
> unprocessed HCP data with our lab software NIAK
> <http://niak.simexp-lab.org/>. My analysis consist of stacking volume
> activation maps as vector of voxels, then correlate each subject vector
> with the rest of the dataset to have a subject by subject correlation
> matrix.
>
>
>
> - What I'm trying to do?
>
> My aim is to repeat the same process above but now with already computed
> activation map from HCP pipeline. So i need a way to transform activation
> surface map to a vector of voxels in order to correlate thse vector between
> subjects.
>
>
>
> If you think that there is a way to correlate activation maps between
> subject directly from surface, I would be happy to know how.
>
>
>
> Thanks
>
> Yassine
>
>
>
> Le mar. 27 mars 2018 à 10:04, Harms, Michael <mha...@wustl.edu> a écrit :
>
>
>
> For the surfaces, why not quantify the activation via the surface area,
> rather than volume?
>
>
>
> Cheers,
>
> -MH
>
>
>
> --
>
> Michael Harms, Ph.D.
>
> -----------------------------------------------------------
>
> Associate Professor of Psychiatry
>
> Washington University School of Medicine
>
> Department of Psychiatry, Box 8134
>
> 660 South Euclid Ave
> <https://maps.google.com/?q=660+South+Euclid+Ave&entry=gmail&source=g>.
> Tel: 314-747-6173 <(314)%20747-6173>
>
> St. Louis, MO 63110 Email: mha...@wustl.edu
>
>
>
> *From: *<hcp-users-boun...@humanconnectome.org> on behalf of Yassine
> Benhajali <yanama...@gmail.com>
> *Date: *Tuesday, March 27, 2018 at 8:58 AM
> *To: *NEUROSCIENCE tim <tsc...@mst.edu>
> *Cc: *hcp-users <hcp-users@humanconnectome.org>
> *Subject: *Re: [HCP-Users] Convert activation cifti data to volume nifti
>
>
>
> Thank you for your reply.
>
> I would like to extract the volume based activation maps from each subject
> and put it as vector and do the same for each subject then stack them all
> in one matrix like this figure. Then, I'll do some clustering on that
> stack.
>
> [image: age.png]
>
>
>
> If you have any hint on how to accomplish that without loosing the benefit
> of surface based registration.
>
>
>
> Best,
>
> Yassine
>
>
>
> Le lun. 26 mars 2018 à 17:20, Timothy Coalson <tsc...@mst.edu> a écrit :
>
> For subcortical structures, it is as simple as wb_command -cifti-separate
> using -volume-all.
>
>
>
> For surface data, you would need to map it back into volume, using that
> subject's surfaces, thereby losing the advantages of surface registration
> (for both analysis and display). You would need to use -cifti-separate
> with -metric, and then use -metric-to-volume-mapping.
>
>
>
> Why are you trying to do this? We might have suggestions of other ways to
> accomplish your task.
>
>
>
> Tim
>
>
>
>
>
> On Mon, Mar 26, 2018 at 12:37 PM, Yassine Benhajali <yanama...@gmail.com>
> wrote:
>
> Hi all,
>
> Any one knows how to extract activation volume in nifti from cifti file
> like this one :
> '139435/FMRI/fMRI_EMOTION/tfMRI_EMOTION_hp200_s4_level2.feat/139435_tfMRI_EMOTION_level2_hp200_s4.dscalar.nii'
>
>
>
> Best,
>
> Yassine
>
> --
>
> Yassine Benhajali
> Doctorant en Neuroanthropologie
> au Laboratoire SIMEXP - http://www.simexp-lab.org/members/
> Université de Montréal, Québec, Canada
> 514 839 0501 <(514)%20839-0501>
>
> _______________________________________________
> HCP-Users mailing list
> HCP-Users@humanconnectome.org
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>
>
>
> --
>
> Yassine Benhajali
> Doctorant en Neuroanthropologie
> au Laboratoire SIMEXP - http://www.simexp-lab.org/members/
> Université de Montréal, Québec, Canada
> 514 839 0501 <(514)%20839-0501>
>
> _______________________________________________
> 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.
>
> --
>
> Yassine Benhajali
> Doctorant en Neuroanthropologie
> au Laboratoire SIMEXP - http://www.simexp-lab.org/members/
> Université de Montréal, Québec, Canada
> 514 839 0501 <(514)%20839-0501>
>
>
> ------------------------------
>
> 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.
>
--
Yassine Benhajali
Doctorant en Neuroanthropologie
au Laboratoire SIMEXP - http://www.simexp-lab.org/members/
Université de Montréal, Québec, Canada
514 839 0501
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