Vertex areas are used in resampling from the native mesh to the 32k
registered mesh (this process occurs on the sphere and aside from the
vertex areas which are calculated on the subjects native mesh and 32k
registered mesh midthicknesses the midthicknesses are not involved).

The small amount of smoothing that is done (2mm FWHM) is done on the
subject¹s 32k registered midthickness.

Conte69 is a group average midthickness that applies to a specific group
of subjects (69 normal controls from the Conte center that we used in the
original T1w/T2w myelin mapping study).

The 32k registered mesh is called 32k_fs_LR (this appears in the file
names of many of the datasets) and refers to a particular surface
topology.

The registration is geographically aligned (in terms of rotation of the
data on the sphere) to a left/right landmark alignment that David did of
the fsaverage surfaces.

Any of the HCP functional CIFTI data can be displayed on any 32k_fs_LR
surface.

The distances between the vertices are not the same across all subjects,
the only thing that is the same is the correspondence between the vertices
(I.e. Vertex 1000 means the same thing across subjects, in so far as the
registration was accurate).

Peace,

Matt.

On 11/21/14, 10:27 AM, "Donna Dierker" <[email protected]> wrote:

>If you compute areas on subject's native mesh, then generally correction
>is not necessary.  But if you compute areas on a mean midthickness
>surface, for example (e.g., computing supratheshold area on group-derived
>clusters/parcels), then correction is appropriate.
>
>The smoothing to which Tim refers is when you have a bunch of
>midthickness surfaces, for example, and you average them to create a mean
>midthickness.  The areas of high variability get smoothed out, so they
>are not as deep/folded as the individual was, hence distances are shorter
>on the mean surface.  Averaging occurs on the atlas mesh -- not native
>mesh.  And Tim is advising you NOT to compute areas/distances on the mean
>midthickness, if you can figure out a way to do it on the individuals.
>This might entail bringing some group-derived ROI (e.g., label.gii) to
>your individual's atlas midthickness (e.g., 164k or 32k mesh surf.gii).
>
>The dtseries.nii files do not contain geometry information.  They link to
>surf.gii files through the mesh they share.  You should pair the
>individual's dtseries.nii with the corresponding midthickness surf.gii.
>Leave the Conte69 geometry out of it, for purposes like these (unless you
>have only group dtseries.nii, in which case you need a mean midthickness
>with vertex-areas).  The distances between the same vertex pairs differ
>quite a bit across subjects.
>
>Regarding the vertex areas, could you provide a link to the pipeline
>source in github where this is invoked in the pipeline?  Few people are
>familiar with this enough to know, but others might be able to shed some
>light if we see how it is called.  I've only seen this feature used when
>dealing with group data, but I'm sure there are usages of which I am
>unaware.
>
>
>On Nov 21, 2014, at 8:59 AM, Benjamin Risk <[email protected]> wrote:
>
>> Great, thank you for the information! To clarify, does the smoothing
>>and area correction occur on the native mesh or Conte69? Do the cortical
>>data in a task file .dtseries.nii correspond to Conte69 midthickness,
>>i.e., the distances between and areas of the vertices are the same for
>>all subjects?
>>
>> Thanks again!
>> Ben
>>
>> On Thu, Nov 20, 2014 at 6:12 PM, Timothy Coalson <[email protected]> wrote:
>> No, we do not have a precomputed file of geodesic distances, we compute
>>them on the fly in any operation that needs them.  Using the
>>-surface-geodesic-distance command on each vertex of interest is
>>certainly one way to find these distances, and may be the best available
>>way depending on the language or tools you intend to use for further
>>analysis.  However, you should use individual surfaces when processing
>>an individual's data, as averaging the surfaces of a group of subject
>>results in smoothing out folding patterns, with more smoothing in higher
>>variability areas, which changes the distances in undesirable ways.
>>
>> The -surface-vertex-areas command does indeed output the vertex areas
>>as they are used in our processing.  Again, you should use individual
>>surfaces when possible.
>>
>> If you want to see how we compute these, the most relevant starting
>>points are here:
>>
>>
>>https://github.com/Washington-University/workbench/blob/master/src/Files/
>>SurfaceFile.cxx , search for "computeNodeAreas"
>>
>>https://github.com/Washington-University/workbench/blob/master/src/Files/
>>GeodesicHelper.h
>>
>> Tim
>>
>> On Thu, Nov 20, 2014 at 4:30 PM, Benjamin Risk <[email protected]>
>>wrote:
>> Hello,
>>
>> I am trying to define a neighborhood structure for vertices in the
>>cortical surface used in the fMRISurface pipeline. My understanding is
>>that the minimally preprocessed subject data are spatially matched to
>>the 32k Conte69 midthickness surface. I would like to use the same
>>distance structure that was used in the preprocessing pipeline as
>>described in Glasser et al (2013) p.121 paragraph two. Does a 32k x 32k
>>matrix (or 29k x 29k excluding medial wall) of distances between
>>neighboring vertices already exist (e.g., sparse matrix with distances
>>for vertices within 3 sigma defined using a 2mm FWHM Gaussian kernel)?
>>If not, is the best way to generate such a matrix by looping through the
>>vertices and using the wb_command -surface-vertex-areas with limit set
>>to 3*0.8493 or similar?
>>
>> On a separate note, I am also interested in the "vertex areas" used in
>>the pre-processing pipeline. Does the command below reproduce these
>>areas?
>>
>> wb_command -surface-vertex-areas
>>Conte69.R.midthickness.32k_fs_LR.surf.gii myfile.gii
>>
>>
>> Many thanks!
>> Ben Risk
>>
>> Graduate Student
>> Department of Statistical Science
>> Cornell University
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