NITRC 1000 Functional Connectomes Project Forum: processing-scripts

ADHD200 database - missing data and other queries

Marietta Papadatou-Pastou — Tue, 05 Jan 2021 6:47:54 GMT

Hello everyone,

We have some trouble with the ADHD200 database and we would really appreciate some help. I have downloaded the attached files and I would like to ask the following questions:

1. Is there an updated version of this database? According to the webpage it was last updated in 2016. One of the reasons why we are asking is that in a number of cells we find the word "pending". Importantly for site "2" the diagnosis is pending, not allowing us to understand which participants are ADHD and which are controls.

2. Do you have information on the means of assessing handedness in each site (e.g., writing hand, the Edinburgh Handedness Inventory, self-report, observation, etc.)?

3. With the term "handedness" do you refer to hand preference or hand skill?

4. For site "5" (= the New York University Child Study Center) the handedness values do not correspond to the key (i.e., 0,1,2), but are continuous. Could you let us know how to interpret these values? Are higher values closer to strong right-handedness or strong left-handedness? Does the value 999 denote a missing value?

5. Again for the data of site "5", a lot of participants seem to have comorbidities, but for a good number of participants the column on additional diagnosis is marked with "N/A". Can we ask why it is non applicable for those participants? This is important for our analysis, because comorbidity is an exclusion criterion.

6. For sites 6 and 8 all participants seem to be right-handed. Is it safe to assume that they were selected for right-handedness?

7. For site "3", we find that participant 2876903 has been allocated the value "3" for handedness, which does not correspond to the key. What would be the handedness of that participant?

8. For site "7" the first 88 participants (participant codes starting with 16) seem to be controls and only 9 participants (codes starting with 25) seem to be a mixture of controls and ADHD. Do these participants correspond to two different studies?

9. For site "8" we see the value "0" under the column DX (we assume it is for the diagnosis). Does this mean this site gave information for typically developing participants only?

10. An important point for us is whether participants were pre-selected to be right-handed (or preferred if so). This would be an exclusion criterion for our analysis. For example, for site "1", 241 out of 245 participants are right-handed, when we would expect 10% to be left-handed. For site "7" only 4 in 98 participants are left-handed.

11. Did all sites use a right vs. ambidextrous vs. left classification of handedness of just the sites where we found a mention of ambidextrous participants? (i.e. only study 3, where one ambidextrous participant is to be found).

I thank you in advance!!

Marietta Papadatou-Pastou
Assistant Professor in Neuropsychology
University of Athens

data_configuration.yml for running default C-PAC pipe on FCon1000 Data

Uri Elias — Wed, 18 Mar 2020 8:28:09 GMT

Hi ,
I'm trying to preprocess the FCon1000 rest data using the C-PAC default pipeline (with minor changes - dropping 1st 4 volumes and adding slice order manually according to the xls).
I've installed the C-PAC successfully via docker on my Win10+WSL2 machine.

Now, CPAC complains the data (as extracted from downloaded tar) is not BIDS compatible. Thus, there seem to be two options ahead:
1- convert files to comply with BIDS
2- write <data_configuration.yml> to fit the filename patterns.

As for the 2nd option - I'm wondering whether there exist <data_configuaration.yml> files that suit the FCon1000 format, so one can just download and run.
As for the 1st option - since I'm a rookie, what's the easiest way to convert?

Thank you all, and may Corona days will end soon

fconn_1000_scripts_ver1.1 download link broken

sshingler — Thu, 20 Jun 2019 12:50:44 GMT

The link to download fconn_1000_scripts_ver1.1 (https://www.nitrc.org/frs/downloadlink.php/2628) does not work. I realize this is an old and deprecated set of scripts, but I need to access them. The 1.1 beta version is available, but I'd like to get the final 1.1 scripts. Are these scripts available anywhere?

Segmentation of OASIS dataset with SPM12

vania karami — Thu, 28 Jun 2018 14:05:46 GMT

I need to have the WM, GM volume of images in OASIS dataset. When I do the segmentation I have this error in Matlab:

Failed 'Segment'
Error using sqrtm (line 35)
Expected input to be finite.
In file "C:\Program Files\MATLAB\R2017a\toolbox\matlab\matfun\sqrtm.m" (???), function "sqrtm" at line 35.
In file "C:\Users\PC4\Desktop\spm12-Copy\spm_preproc8.m" (v7172), function "spm_preproc8" at line 673.
In file "C:\Users\PC4\Desktop\spm12-Copy\spm_preproc_run.m" (v6365), function "run_job" at line 131.
In file "C:\Users\PC4\Desktop\spm12-Copy\spm_preproc_run.m" (v6365), function "spm_preproc_run" at line 41.
In file "C:\Users\PC4\Desktop\spm12-Copy\config\spm_cfg_preproc8.m" (v6952), function "spm_local_preproc_run" at line 450.

The following modules did not run:
Failed: Segment

DO you know what should I do?

ABIDE NIAK preprocessing issues - NYU dataset

Amritha Harikumar — Thu, 21 Dec 2017 6:26:41 GMT

Hi,

I am trying to preprocess raw datasets from abide using the NIAK pipeline ; however, my mean FD values do not match what is in the abide data spreadsheet for comparison. Is there any way I can obtain a parameter list, so we can replicate the exact results downloaded off of NITRC? I've attached the motion value comparisons from my pre-processing efforts, and what is given in the dataset. Thanks!

Google program for CPAC developers still open

Ivan Roi — Wed, 25 Mar 2015 14:32:38 GMT

Dear all,

The application period for Google Summer of Code (GSoC) projects with INCF (International NeuroInformatics Facility) will still be open for few days, and we encourage interested candidates to apply to this exciting opportunity.
Every year Google invites students to embark with an open-source institution of their choice for few months, and develop code in a project of the interest. These experiences make a real difference, boosting students' careers and endeavours in the process.
We would welcome interested students to direcly address any questions or enquiries, as well as intention to apply, to Dr Ivan J Roijals (ij.roijals@gmail.com).

[b]Toolboxing complexity for connectomes: New code for big samples in C-PAC[/b]

C-PAC (Configurable Pipeline for the Analysis of Connectomes, http://fcp-indi.github.io/) is a new, developing tool designed to study connectivity in brain images, transformed into connectomes. It allows us to work with big datasets using computer clusters. Integrating some of the most successful imaging environments to date (FSL, AFNI, ANTS), and advancing several innovative methods in preprocessing (automatic quality control, motion correction, regional homogeneity), it provides researchers with the chance to test new network and dynamical properties. Complexity measures (graph and non-linear series) are currently among the best tools to study functional network properties and the design of the brain topological properties.

[b]Aims[/b]

In contact with mentors, C-PAC developers and its forums, the successful student will develop very valuable and innovative tools that will help researchers to perform new analysis in connectomics:

- To add/expand a set of python scripts (within the scope of the developers' documentation; http://fcp-indi.github.io/docs/developer/developer/index.html), oriented to the analysis of non-linear series' within the time series workflow, thus giving a comprehensive set of analysis tools in this area to the researcher. Some of the proposed, such as sample and transfer entropies, multifractal analysis and surrogate testing, would help to test dynamical properties not available in current packages.

- Alternatively, this project is also aimed to produce code and integration of new network connectivity (generically within centrality and complexity structure), complementing the existing ones, in the frame of C-PAC's analysis/networks workflow and providing a more comprehensive set of tools for the study of connectomes.

- To put the test these tools to test and document its performance with the study of available databases (ie. 1000 connectomes datasets) and the properties that pinpoint in brain function. It will also be expected to help in the integration of workflows and components, possibly interacting with the C-PAC community.

[b]Skills[/b]

- Essential: Hands-on experience in python, possibly in Nipype and sofware developing. Familiarity with cluster and grid computing and software carpentry / collaborative software (Github). Basic knowledge on scientific implementation. Basic knowledge on functional imaging processing. Knowledge in graph methods, time-series complexity analysis and information theory.
- Desirable: C++ and/or Fortran, Perl, Javascript, CSS. Working knowledge on imaging preprocessing and frequency analysis. Knowledge on imaging packages (FSL, AFNI).

[b]Mentors[/b]

Ivan J Roijals (KI-INCF, ij.roijals@gmail.com). Co-mentors: Cameron Craddock (Child Mind Institute, cameron.craddock@gmail.com), Victor M Eguiluz (IFISC-UIB, victor@ifisc.uib-csic.es)

preprocessing for connectome analyses

Angela Favaro — Fri, 20 Mar 2015 17:14:01 GMT

Dear all,
I am looking for suggestions about how to change/adapt preprocessing scripts of the 1000 functional connectomes to perform connectome analyses.
I probably need to avoid the smoothing step and global signal regression. But I do not know if other changes are necessary

I would also be interested to perform decomposition of time series into distinct frequency bands using the maximal overlap wavelet transform. How can I implement this on my resting-state data?

Thank you for any help or suggestion

Angela

RE: How to include motion-related spike regressor

Maarten Mennes — Wed, 17 Sep 2014 8:52:41 GMT

Hi,

in the fcon-1000 preprocessing scripts it is not possible to add motion-related spike regressors (if you know what you're doing it is possible to implement it by hacking the 5_nuisance.sh script). In addition, I'd like to remind that the fcon-1000 scripts are no longer supported, and are actually a bit outdated when it comes to resting state fmri preprocessing. A good alternative would be to look at CPAC at http://fcp-indi.github.io/

hth,
Maarten

How to include motion-related spike regressor

yikai wang — Tue, 16 Sep 2014 2:48:14 GMT

I am trying to consider the motion-related spike regressors whenever a volume-to-volume displacement was > .25mm. Is it possible for this preprocessing scripts to do it? How?

RE: converts NIFTI_datatype=4 (INT16) to float

peter lee — Fri, 30 May 2014 18:08:40 GMT

thanks Maarten,
I have viewed the previous discussion in this forum,
and got lots of information about slice timing correction now.
I still have one question is that, could I get the acquisition order from the raw data (e.g., dicom),

Have a good day..

Peter