Thank you Tim. I agree about effect size maps being better, but reviewers
always want to know what is significant (they are set in their ways!!) So maybe
we can do both; an effect size map and then .95-1 in the corr p map?
On Mar 16, 2018, at 4:59 PM, Timothy Coalson
You can do whatever you need to to satisfy your reviewers, of course.
Showing both in one panel was the idea behind turning the significant
regions into label outlines. Take a look at page 5 here:
https://wustl.app.box.com/s/ti46uqqlukqnh4u97aw74r53r7p8xu3c
In this case, the very large group
Load both of the volumes into wb_view (high-res mask and low-res fMRI - you
may want to separate out a single frame from the fMRI to keep memory usage
down) and see if they align with each other (if they don't display
correctly, turn on oblique volume drawing mode). If they do align, the
answer
Since the extent that passes significance tests is dependent on number of
subjects and other statistical power considerations, we instead recommend
viewing the effect size (beta) map. You can overlay outlines of what
passed the significance threshold by making that into a label file with
Perhaps if this were done with wb_command -volume-resample it would work
better, but Tim would have to comment on this.
Matt.
From: HERACLES PANAGIOTIDES >
Date: Friday, March 16, 2018 at 12:11 PM
To: Matt Glasser >
To Whom it may concern,
I am attempting to run the diffusion processing pipeline, by using the scripts
from the Washington University github.
In particular, I am using the DiffusionPreprocessingBatch.sh script, from the
Examples folder. We successfully managed to run the structural
Thanks for the recommendation Matt!
Pedro, the ciftify toolbox link is here (https://edickie.github.io/ciftify).
The toolbox started with exactly with what you are suggesting (modifying
the .sh files to make them run without T2w images). Over time we ended up
translating the key parts to python
Hi,
In documentation for randomise, when viewing the 1-p results in FSLView the
min/max display range should be set to 0.95/1.0 so that values less than 0.95
(equivalent to p>0.05) are not shown. If these are corrected values (i.e.
corrp) then the visible areas correspond to the statistically
Dear HCP experts,
In the context of my PhD thesis (using HCP data), I had some questions about
MEG processing pipelines.
In my research, I somehow need the MEG data during motor task, in the source
space (i.e. after beamforming), for each trial and each individual separately.
It seems that the
We don’t have such a method at this time.
Peace,
Matt.
From: Xavier Guell Paradis >
Date: Thursday, March 15, 2018 at 6:50 PM
To: Matt Glasser >,
I would recommend the ciftify toolbox if your data do not meet HCP Pipelines
acquisition requirements (lacking highres T2w scan and or Fieldmap). The
ciftify toolbox is currently beta, but should be fully available in the very
near future (Erin Dickie the author is CCed and can give more
Why can’t you use an MNI space accumbens mask?
Peace,
Matt.
From:
>
on behalf of HERACLES PANAGIOTIDES >
Date: Friday, March 16, 2018 at 8:04 AM
To: HCP
Dear all,
I have a dataset that I wish to use with the HCP pipeline scripts from the
repository in https://github.com/Washington-University/Pipelines, but I
don't have the T2w images for the subjects. Is it possible (perhaps with
some modification on the .sh files) to use pipeline without the
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