As Matt says, figure 2 is where we show that lower, legacy resolutions
would also benefit from surface-based analysis.  This was a late addition
to the paper, so there isn't as much coverage of lower resolution.

Figure 7 only looks at all of cortex as a single entity, so it doesn't
capture problems with crossing sulcal banks, or areas not being lined up.
The main point of it is to show that high-resolution data does much better
with surface-based methods than it does with volume-based methods, since
tissue alignment across subjects is only a problem for volume-based
methods.  Additionally, the distribution of cortical signal capture across
the brain is more uniform with surface-based methods, while volume-based
methods do much worse in some regions than in others.

Figure 8 does not represent different resolutions, it uses 2mm resolution
(HCP fMRI), the "+ 4mm" refers to adding smoothing to the analysis
(surface-based smoothing for MSMAll, volume-based for FNIRT).  Smoothing is
a traditional part of many processing pipelines, and we consider such a
practice to be harmful, especially when the smoothing is volume-based.

Tim


On Fri, Jun 1, 2018 at 8:06 PM, Joseph Orr <[email protected]> wrote:

> This is a great paper for encouraging the adoption of HCP-style
> acquisitions for future studies, but I'm curious about the benefit of
> applying the surface-based approach to existing, traditionally acquired
> datasets. In Figure 7 of your paper you simulate traditional acquisition
> resolutions which is very helpful. But these simulations are still assuming
> HCP-style sub-millimeter T1s and T2s for the surface registration. In a
> recent dataset I collected .8mm T1s but we didn't collect T2s (not my
> decision).
>
> What are your recommendations for more traditional study acquisitions like
> this? I think this question is what you're getting at in Figure 8, but I
> need to spend a little more time with the paper. Without a T2 is FreeSurfer
> my best bet?
>
> Thanks,
> Joe
>
> --
> Joseph M. Orr, Ph.D.
> Assistant Professor
> Department of Psychological and Brain Sciences
> Texas A&M Institute for Neuroscience
> Texas A&M University
> College Station, TX
>
> On Fri, Jun 1, 2018 at 7:12 PM, Glasser, Matthew <[email protected]>
> wrote:
>
>> I would note that we don’t recommend mapping group average volume data to
>> group average surfaces.  It is a much better idea to map the data onto the
>> individuals' surfaces and register it on the surface (and also avoid
>> smoothing in the volume or even better avoid smoothing entirely):
>>
>> See this article currently in press at PNAS: https://www.biorxiv.org/
>> content/early/2018/04/23/255620
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.biorxiv.org_content_early_2018_04_23_255620&d=DwMF-g&c=ODFT-G5SujMiGrKuoJJjVg&r=ZKy1VO33u0kvO-PqY1gpb9Ld-AGhtT8c9PAcpsEyp70&m=NDSQ3kMMhk_BcjZ91RPExirFBMmqlMSPFqIRXr0e6Mk&s=Op6bJ6Q2t5EvGlDljAWbc9tKe1pHdybU1cXQUKBjEsA&e=>
>>
>>
>> Peace,
>>
>> Matt.
>>
>> From: <[email protected]> on behalf of Joseph Orr <
>> [email protected]>
>> Date: Friday, June 1, 2018 at 6:37 PM
>> To: Kristian M Eschenburg <[email protected]>
>> Cc: HCP Users <[email protected]>
>> Subject: Re: [HCP-Users] Conte69 164k and 32k mesh
>>
>> I'd recommend using the S900 group maps available at the BALSA site which
>> is referred to on the caret page: https://balsa.wustl.edu/
>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__balsa.wustl.edu_&d=DwMF-g&c=ODFT-G5SujMiGrKuoJJjVg&r=ZKy1VO33u0kvO-PqY1gpb9Ld-AGhtT8c9PAcpsEyp70&m=NDSQ3kMMhk_BcjZ91RPExirFBMmqlMSPFqIRXr0e6Mk&s=nertDHfdcmNZRWyvrQ2xkwan957VrE9FyosIzhKP5Mw&e=>
>>
>> You can register volumetric data to the surfaces following the
>> instructions in the Workbench tutorial or this blog post:
>> http://mvpa.blogspot.com/2014/03/connectome-workbench-adding-volumes.html
>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__mvpa.blogspot.com_2014_03_connectome-2Dworkbench-2Dadding-2Dvolumes.html&d=DwMF-g&c=ODFT-G5SujMiGrKuoJJjVg&r=ZKy1VO33u0kvO-PqY1gpb9Ld-AGhtT8c9PAcpsEyp70&m=NDSQ3kMMhk_BcjZ91RPExirFBMmqlMSPFqIRXr0e6Mk&s=-3VEDq5QbXj8H94XYv4qckbANmT62lOByFhcIoukpWo&e=>
>>
>> I've found workbench to be more user friendly than caret, assuming that's
>> what you were intending to use.
>>
>> Joe
>>
>> --
>> Joseph M. Orr, Ph.D.
>> Assistant Professor
>> Department of Psychological and Brain Sciences
>> Texas A&M Institute for Neuroscience
>> Texas A&M University
>> College Station, TX
>>
>> On Fri, Jun 1, 2018 at 5:48 PM, Kristian M Eschenburg <[email protected]>
>> wrote:
>>
>>> Hi HCP Admins
>>>
>>> Where can I download the 164k and 32k resolution Conte69 template
>>> meshes?  I'm trying to register data I've acquired to the same MNI
>>> space-surfaces as the HCP data.  I searched the SumsDB site (
>>> http://brainvis.wustl.edu/wiki/index.php//Caret:Atlases/Conte69_Atlas
>>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__brainvis.wustl.edu_wiki_index.php__Caret-3AAtlases_Conte69-5FAtlas&d=DwMFaQ&c=ODFT-G5SujMiGrKuoJJjVg&r=ZKy1VO33u0kvO-PqY1gpb9Ld-AGhtT8c9PAcpsEyp70&m=VgTjzj6GtNY5OkkbA0JzFKw5Q0JILeOmYmRx6TQulFY&s=F3ndSFg5e0RefqpYKJ5c2JOgCVlaCJP6wVu0gQQHqXc&e=>)
>>> and it seems there was a "catastrophic failure" w.r.t to making this data
>>> freely available.
>>>
>>> Any information is appreciated.
>>>
>>>
>>>
>>> Kristian
>>>
>>> _______________________________________________
>>> HCP-Users mailing list
>>> [email protected]
>>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>>> <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.humanconnectome.org_mailman_listinfo_hcp-2Dusers&d=DwMF-g&c=ODFT-G5SujMiGrKuoJJjVg&r=ZKy1VO33u0kvO-PqY1gpb9Ld-AGhtT8c9PAcpsEyp70&m=NDSQ3kMMhk_BcjZ91RPExirFBMmqlMSPFqIRXr0e6Mk&s=wCVk1igEI_a0pOwWL3FwdqRffyD5_iX1hkVHWMC_owE&e=>
>>>
>>
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>>
>
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