Re: [HCP-Users] De-activations in "LANGUAGE" Task Contrast Maps

[Glasser, Matthew]

Hi Chris, The task data were not cleaned with ICA+FIX or even movement parameter regression.  As to why there is a correlation between the ventricles and a given contrast, that’s puzzling to me as well, but the point is that a strongly structured ventricle signal would get identified and removed by ICA+FIX (this is what it is designed to do, and it knows where the ventricles are in each subject).   Whether or not a volume-based analysis is useful for QA, in an ideal world we would have already taken care of this issue for users and a cortical volume-based analysis is not appropriate for primary neuroanatomical results intended to be interpreted in relation to cortical functional areas or compared across studies for the reasons I stated (at least in my opinion).  Perhaps the precipitating issue of structured noise in the task data needs to be revisited internally, but I know the people who would do any testing and analyses have many other competing priorities and I certainly could only provide advice for addressing that problem.   Peace, Matt. From: Chris Filo Gorgolewski <krzysztof.gorgolew...@gmail.com> Date: Saturday, March 14, 2015 at 5:31 PM To: Matt Glasser <glass...@wusm.wustl.edu> Cc: vanessa sochat <vsoc...@stanford.edu>, "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>, Russell Poldrack <poldr...@stanford.edu> Subject: Re: [HCP-Users] De-activations in "LANGUAGE" Task Contrast Maps Hi Matt, Thanks for a quick reply. On Sat, Mar 14, 2015 at 3:01 PM, Glasser, Matthew <glass...@wusm.wustl.edu> wrote: If you don’t want ventricle activations in the task fMRI data, it would be good to clean the data with something like ICA+FIX which will remove spatially specific structured noise (such as whatever is causing the ventricles to light up) prior to fitting the GLM.  There are other stimulus correlated artifacts in the task data (uncorrelated artifacts would tend to get averaged out in the GLM analysis) such as strong deactivation in orbitofrontal regions in the Tongue movement contrast.  Use of ICA+FIX in task analysis was looked at some inside the consortium, but I’m not sure if there was ever a focus on seeing that stimulus correlated artifacts were being removed (vs just seeing how Z-stats changed with cleanup, which they don’t much since most of the variance in HCP fMRI timeseries is unstructured).   Just to clarify - my understanding was that the preprocessed task data distributed by HCP was "cleaned" using ICA+FIX. Is that not correct? If ICA+FIX was not not used on task data do you have any ideas why would there be such a strong relation between the stimulus and CSF in the ventricles? Just to put it into perspective - the deactivation in the ventricles is more significant than the activation in the language areas. Also it makes me sad to see you aren’t using the CIFTI data, which are substantially more accurately registered across subjects and don’t have the unnecessary blurring with white matter and CSF signals (and in 3D across sulci and gyri) induced by unconstrained volume-based smoothing as misalignment between functional areas.  The volume-based data simply don’t allow you to take advantage of the high spatial resolution that the HCP data were acquired with like the CIFTI data do, so you’re missing out on all the cool new things you can see. I agree using CIFTI has many advantages, but it would also make one completely miss the artefact Vanessa run across. Therefore I would argue, at least for QA purposes, that there is a justification for using volumes.   Best, Chris   The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users