Hi Matt,
yes I mean homotopic connections.
The individual dense connectivity map in the image you sent is not
available from the HCP DB, am I wrong?
Was this computed from dense timeseries ICA-FIX as provided online using
the wb_command -cifti-correlation? Does it add global signal regression to
get the negative parts?
Maybe the way I extract the signal from cortical ROIS is wrong, but I
heavily rely on the cifti header to determine which rows belong to each
ROIs so I used the "brain models" to get the IndexOffset and IndexCount of
the different brain models, then used the
??????.?.aparc.a2009s.32k_fs_LR.label.gii to get the ROIs in the surface
brain models using only the vertices listed in the CIFTI_STRUCTURE_CORTEX_*
brain model NodeIndices xml element (which certainly exclude the filled
holes in surface and fs medial wall ROI).
for instance in the 101915 first scan LR , there are the following brain
models:
model type structure
index count
CIFTI_MODEL_TYPE_SURFACE CIFTI_STRUCTURE_CORTEX_LEFT 0 29696
CIFTI_MODEL_TYPE_SURFACE CIFTI_STRUCTURE_CORTEX_RIGHT 29696
29716
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_ACCUMBENS_LEFT
59412 135
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_ACCUMBENS_RIGHT
59547 140
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_AMYGDALA_LEFT 59687
315
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_AMYGDALA_RIGHT
60002 332
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_BRAIN_STEM 60334
3472
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_CAUDATE_LEFT 63806
728
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_CAUDATE_RIGHT 64534
755
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_CEREBELLUM_LEFT
65289 8709
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_CEREBELLUM_RIGHT 73998
9144
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_DIENCEPHALON_VENTRAL_L
83142 706
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_DIENCEPHALON_VENTRAL_R
83848 712
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_HIPPOCAMPUS_LEFT 84560
764
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_HIPPOCAMPUS_RIGHT 85324
795
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_PALLIDUM_LEFT 86119
297
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_PALLIDUM_RIGHT
86416 260
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_PUTAMEN_LEFT 86676
1060
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_PUTAMEN_RIGHT 87736
1010
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_THALAMUS_LEFT 88746
1288
CIFTI_MODEL_TYPE_VOXELS CIFTI_STRUCTURE_THALAMUS_RIGHT
90034 1248
but the problem might be in the mapping of ROIs from the aparc.a2009s+aseg
gifti files.
Sorry if it is not clear but I had to reverse engineer the stuff so I may
have done it wrong and it might not be possible to do it without some prior
hidden in the workbench.
Thanks for you insight on this.
Basile
On Thu, Dec 5, 2013 at 12:52 AM, Glasser, Matthew
<[email protected]>wrote:
> I'm not sure what you mean by homologous connectivity. Does that mean
> connectivity between corresponding parts of the hemispheres (like is shown
> in the attached png from subject 101915—seed vertex is white, corresponding
> vertex is green)?
>
> These data are acquired with a very fast TR (0.720ms), which means that
> the movement parameters may pick up physiological motion effects in
> addition to actual subject movements. In slower TR dat sets these are
> aliased into the timeseries so you cannot see them.
>
> Peace,
>
> Matt.
>
> From: basile pinsard <[email protected]>
> Date: Wednesday, December 4, 2013 4:24 PM
> To: "[email protected]" <[email protected]>
> Subject: [HCP-Users] Q3 rfMRI
>
> Hi all,
>
> trying to process individual rfMRI from HCP, we found unexpected results
> of connectivity:
> - almost no homologous connectivity (see attachment) either by taking
> mean timeseries in aparc.a2009s+aseg rois(as store in fsaverage32k gifti
> files for surfaces) or by computing the 30gigs voxelwise dense matrix
> zscore and averaging in the same rois.
> We did it with and without regressing out mean gray timecourse from the
> same dense timeseries because it seems to influence largely the
> connectivity.
> We also did in on the base preprocessed, and ica-fixed data to check,
> results are quite similar.
> Will the pipeline used for preprocessing be released publicly at some
> point?
>
> - the motion estimated is quite shaky and unrealistic (for example the
> scans of subject 101915 enclosed), do you know which method was used for
> realignment of the data? If this estimated motion is used both for
> interpolation of data and regression of nuisance signal, this has certainly
> huge effect on the connectivity.
>
> Was the same data/preprocessing used for estimating the 40subject dense
> correlation matrix ? This has expected connectivity structure.
>
> Thanks for your help.
> Best.
>
> Basile Pinsard.
>
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