This issue of what kind of data and how much is something we plan to
investigate in detail for MSMAll (and the cortical areal classifier).
Matt.
From: "Harms, Michael"
Date: Thursday, May 9, 2019 at 4:41 PM
To: "Glasser, Matthew" , Maria Sison
, Steve Smith
Cc: HCP 讨论组
Subject: Re:
While I’m not surprised that the ICCs would be lower for an anatomical-based
measure for MSMAll than MSMSulc, I am surprised by the magnitude of the change
(from 0.9 to 0.65), especially for a parcellated analysis, since only changes
in the precise border of the parcellations should be
Not running sICA+FIX might well be a part of the problem. The TR is quite long
as Steve says, which will limit the accuracy of sICA+FIX cleanup some also.
Also, surface area and thickness might prefer MSMSulc due to correlations with
folding patterns. Myelin, task, and resting state fMRI
Thank you so much, this is very helpful and interesting to think about. We
concatenated rest and tasks and regressed out tasks to get around 1000 TRs of
pseudo-rest which we then used for MSMAll. Still not nearly as much as HCP, but
I would be interested to hear what a ballpark minimum data
Hi - probably the single primary thing is number of timepoints - though things
like TR and spatial resolution will also affect this.
My guess is still that probably you don't have enough timepoints here to get
decent single-subject RSN maps (decen enough for MSMALL that is). Emma or Matt
Hello,
Here’s our rfMRI protocol: each participant was scanned using a Siemens Skyra
3T scanner equipped with a 64-channel head/neck coil. A series of 72
interleaved axial T2-weighted functional slices were acquired using a 3-fold
multi-band accelerated echo planar imaging sequence with the
Hi - what is your rfMRI protocol? It might be that you're right that the
difference is in the preprop - but my first guess might be that - if the rfMRI
data is not as high quality as HCP rfMRI data - it might not be good enough to
reliably drive MSMALL?
Cheers.
> On 9 May 2019, at 14:45,
Dear experts,
We have run the HCP minimal preprocessing pipelines on our data (1 mm isotropic
T1w and FLAIR + rest and 4 tasks) and compared test-retest reliability for
MSMSulc and MSMAll in 20 subjects. Specifically, we looked at intraclass
correlations for parcellated cortical thickness and
Additionally, this may already be fixed in the latest master (as of 3 weeks
ago).
Tim
On Thu, May 9, 2019 at 1:47 PM Timothy Coalson wrote:
> The quick solution is to add that path to your default matlab path, with
> the added benefit that you can then use ciftiopen and related in your own
>
The quick solution is to add that path to your default matlab path, with
the added benefit that you can then use ciftiopen and related in your own
code. Our setups always have a version of these functions in the default
matlab path, which is probably why we missed this.
Tim
On Thu, May 9, 2019
Hi,
When running MSMAllPipelineBatch, it ultimately calls the matlab function
ComputeVN (in my case, running the matlab interpreted version) which then
crashes because it doesn't recognize the "ciftiopen" function. Obviously it
can't find the directory where the function is. I have already
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