Hi David,
The conditions are coded in the TAB.txt files in the public data release.
BILLIARD-A.AVI Random
BILLIARD-B.AVI Random
COAXING-B.AVI Mental
Dancing.AVI Mental
DRIFTING-A.AVI Random
DRIFTING-B.AVI Random
Fishing.AVI Mental
MOCKING-A.AVI Mental
MOCKING-B.AVI Mental
Random mechanical.AVI
I believe that the Open Access Data Use terms
(https://www.humanconnectome.org/study/hcp-young-adult/document/wu-minn-hcp-consortium-open-access-data-use-terms)
require that anyone receiving the data must have first agreed to the Open
Access Data Use Terms. If my understanding is correct, that
PALM does provide an option to do spatial cluster correction using TFCE.
Currently, that is the only cluster-based multiple correction method available
in CIFTI grayordinate space. Otherwise, you could use conduct parcellated
analyses and correct for the number of parcels, or conduct
Hello Xinyang,
Most likely, you haven’t accounted for “NLR”, which stands for “no logged
responses”. If the response period timed out without an overt response, we
can’t be sure whether the participant would have made a correct response or an
error response. Since NLRs are neither correct or
Hi Daniel,
I agree with Matt that it’s probably not a good idea to ‘cut’ the data into
Language-only pieces. FMRI data are always relative, meaning that they only
have meaning in comparison to other conditions.
There is additional information about the task design in the Barch et al (2013)
Hello Iris,
If you’re interested in individual subject estimates of the face-tool contrast,
I don’t believe that you can create new contrasts without running your own GLM.
(Perhaps other users will be familiar with a different method.)
However, if you are interested in the average difference
Hi Daniel,
The Language task and Emotion tasks were designed with no blocks of resting
fixation. The intention was to directly contrast STORY vs. MATH in the Language
task, and FACES vs. SHAPES in the Emotion task. If possible, you should
consider using only the STORY-MATH and FACES-SHAPES
Hi Manasij,
We’ve discussed this in some detail with the folks at FMRIB. They have long
known that the cost function in FLIRT (and MCFLIRT) is biased toward zero for
very small motions. However, when the movement regressors have long series of
zeroes, the motion corrected time series does not
of Medicine
Department of Psychiatry
Phone: 314-362-7864
Email: gburg...@wustl.edu<mailto:gburg...@wustl.edu>
On Nov 12, 2018, at 4:25 PM, Burgess, Gregory
mailto:gburg...@wustl.edu>> wrote:
If you want to review the stimuli used in the Relational task, you can always
download th
If you want to review the stimuli used in the Relational task, you can always
download the 3T E-Prime scripts from the ConnectomeDB.
https://db.humanconnectome.org/app/action/ChooseDownloadResources?project=HCP_Resources=Scripts=HCP_TFMRI_scripts.zip
--Greg
The rationale for using a blocked design versus event-related design is
discussed in Barch et al. 2013. In general, blocked designs have higher
sensitivity than event-related designs. The event-related design showed the
same pattern of activation, but was less sensitive. Therefore, the blocked
Hello Katerina,
- The first row in the SyncSlide.OnsetTime column reflects the onset of the
first TR in E-Prime clock (i.e., the first trigger). This time must be
subtracted from all other timestamps in the TAB.txt to determine the amount of
time since the first trigger / first BOLD volume.
Hi Yann,
In a GLM, the baseline / intercept / B0 reflects the mean of the residual BOLD
time series after removing variance explained by all other regressors. Beta
weights for other conditions can be conceptualized as BOLD differences between
those conditions and the baseline.
When the task
That’s correct. There is no need to adjust the timing of any of the EV files.
--Greg
Greg Burgess, Ph.D.
Staff Scientist, Human Connectome Project
Washington University School of Medicine
Department of Psychiatry
Phone:
The scripts are currently available for download at:
https://www.humanconnectome.org/study/hcp-lifespan-aging/project-protocol/task-protocols-hcp-aging
https://www.humanconnectome.org/study/hcp-lifespan-development/project-protocol/task-protocols-hcp-development
Currently, there is not a
ty School of Medicine
Department of Psychiatry
Phone: 314-362-7864
Email: gburg...@wustl.edu<mailto:gburg...@wustl.edu>
[X]
--
Meizhen Han
PhD Candidate
Center for MRI Research
Peking University
Beijing, China
At 2018-02-24 01:57:49, "Burgess, Gregory"
<gburg...@wustl.edu<mai
There is no difference between the duration of the E-Prime tasks and the
duration of the BOLD time series from the scan. There is likely a
misunderstanding of what the duration should be, but I can’t help without
knowing specifically what doesn’t line up in your opinion.
There have been two
Hi Xinyang,
The accuracy and RT for individual stimuli within a scan are in the
preprocessed directory for that scan (i.e., preproc resources). The files end
with “TAB.txt”, and are tab-delimited E-Prime outputs. If you need detail about
the variables contained in those TAB.txt outputs, you
The Language task was not designed to be an alternating (ABAB) blocked design.
The _first_ run had alternating blocks (ABAB) simply by chance.
--Greg
Greg Burgess, Ph.D.
Staff Scientist, Human Connectome Project
Washington
ork my way back
> up to the surface, but as this requires quite a bit more work I was hoping to
> avoid this.
>
> Reinder
>
> On Thu, Mar 23, 2017 at 2:00 PM, Burgess, Gregory <gburg...@wustl.edu> wrote:
> When we called this a “fake” NIFTI, that was a misnomer. It is a real NIFTI
>
When we called this a “fake” NIFTI, that was a misnomer. It is a real NIFTI
file. The issue is that the voxels are not ordered in space as you would expect
from a real brain. So, your software should work with it, as long as you’re not
trying to do processing along a spatial dimension (e.g.,
Hi Yann,
Thanks for looking into this. We will take some time to review the data files
and processing scripts. If there’s need for an update, we’ll announce that to
this list, and post the information on the known issues wiki page.
Thanks,
--Greg
Hi Andrew,
To be clear, ICA-FIX may not improve task fMRI data when it is run separately
on each tfMRI scan. MELODIC separates signal from noise better when there are
tons of time points going into the ICA, which isn’t always the case with single
tfMRI scans. Also, the confound regression will
dtseries.nii STDEV
> /stdevcopeMOTORTMINUSCUE.dscalar.nii;
> -cifti-math '(mean) / stdev' /cohendmapMOTORTMINUSCUE.dscalar.nii -var mean
> /meancopeMOTORTMINUSCUE.dscalar.nii -var stdev
> /stdevcopeMOTORTMINUSCUE.dscalar.nii
>
> Thank you very much,
> Xavier.
> ___
I thought that contrasting each effector against the average of the others
(e.g., RH-AVG) was a more-effective control to isolate motor-specific regions.
If you are still interested in contrasting each effector versus the cue
(controlling for visual activation without controlling for other
The error may be referring to the location specified in Aspera Connect >
Preferences > Transfers > Save downloaded files to:
[cid:4A4CB0FE-ED27-4CD2-A866-FFEE544CC7FB@wucon.wustl.edu]
Does that location in your preferences exist?
--Greg
Hello Bo-yong,
We did not directly measure the size of stimuli for the working memory
paradigm. Unfortunately, the same scanner environment is no longer available,
so we can’t really measure it in retrospect.
--Greg
Greg
HCP processing does not conduct low-pass filtering for either minimally
preprocessed or FIX-cleaned data. However, low pass temporal filtering is
probably not necessary, and is not recommended by the HCP consortium.
One goal of FIX is to selectively remove high frequency noise, but keep other
airly straightforward with the -stim_times_IM options for
> 3dDeconvovle. Does something comparable exist for FEAT or do I have to code
> each time point for each individual as a separate regressor in the subject's
> fsf file before running feat_model?
>
> Thanks,
> Michael
> From: Burgess, Greg
In general, if you do a conversion from CIFTI to (fake) NIFTI, you can conduct
any timeseries analyses using any tools you would desire, and then convert back
to CIFTI. Spatial processing (spatial smoothing, defining clusters, etc.) needs
to happen in CIFTI space using wb_command.
--Greg
Hi Ferdaus,
It doesn’t appear that you’re using FIX data, but I think you should seriously
consider doing so. To be clear, we believe that using FIX-denoised timeseries
data is a replacement for / better alternative to: 1) regression of head motion
estimates, 2) frame censoring / scrubbing of
es, or if
> this is specific to our site.
>
> Cheers,
>
> Andrew
>
> On Thu, Oct 6, 2016 at 11:37 AM, Burgess, Gregory <gburg...@wustl.edu> wrote:
> I haven’t had a chance to look at those new files, so I’d be interested to
> hear more about your experience.
>
I haven’t had a chance to look at those new files, so I’d be interested to hear
more about your experience.
If you’re not familiar with it, you should check out
https://github.com/CMRR-C2P/MB/blob/master/readCMRRPhysio.m .
One thing to note, at least with the legacy files, the time stamp in
HCP did not have a task that was geared toward response inhibition.
Furthermore, although it’s alluring to believe that a single parcel will
encapsulate all of response inhibition, it’s doubtful.
Why not select a set of parcels in and near IFG, and correct for multiple
comparisons? Use a
e feat_model.
Thank you,
Michael
On Thu, Sep 22, 2016 at 3:35 PM, Burgess, Gregory
<gburg...@wustl.edu> wrote:
If you’re referring to what is sometimes called a “state-item” design (cf.
http://www.nil.wustl.edu/labs/schlaggar/Publications_files/MIxedBlockPaper_Final.pdf), you shoul
Hi Michael,
A few things:
1) Matt’s point about the increased activation estimates in visual cortex is a
good one. There is increased signal in occipital cortex in functional
connectivity analyses that do not assume a response shape. In part, this may
result from the back of the head being
n Connectome Project
Washington University School of Medicine
Department of Neuroscience
Phone: 314-362-7864
Email: gburg...@wustl.edu<mailto:gburg...@wustl.edu>
On Sep 12, 2016, at 1:50 PM, Burgess, Gregory
<gburg...@wustl.edu<mailto:gburg...@wustl.edu>> wrote:
Hi Michael,
I just wan
Hi Michael,
I just want to verify that you are trying to use PALM for “higher-level” group
analyses. PALM is not currently able to conduct “lower-level” timeseries
analyses. You currently need to use the HCP task fMRI pipelines for that.
If you are attempting group analyses, it might be
fortunately I will not be able to attend this year, but I look forward to
> seeing those examples afterward.
>
> Thank you,
> Michael
> From: Burgess, Gregory <gburg...@wustl.edu>
> Sent: Thursday, August 4, 2016 10:05:47 AM
> To: Michael F.W. Dreyfuss
> Cc: hcp-users@humanc
it would
rate spike-like ICA components as noise.
--Greg
Greg Burgess, Ph.D.
Staff Scientist, Human Connectome Project
Washington University School of Medicine
Department of Psychiatry
Phone: 314-362-7864
Email: gburg...@wu
PALM isn’t intended to replace the level 1 (timeseries) analysis. Permutation
testing doesn’t handle the autocorrelated timeseries appropriately, because
time points are not truly exchangeable.
It should be possible to do a repeated measures analysis in PALM (treating
acitvation estimates from
The FIX code includes a hcp_fix wrapper script, which you could run on the task
fMRI time series data. It should be pretty straightforward.
However, the fact is that the 3T task data was not denoised by FIX because the
zstat maps generally _decrease_ in statistical significance after FIX in
> On Aug 2, 2016, at 10:17 AM, Michael F.W. Dreyfuss
> wrote:
>
> Hi, I have some basic questions about the movement parameters that are put
> out by the HCP preprocessing scripts.
>
> 1) What is the difference between Movement_Regressors_dt.txt and
>
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