C-PAC Version 1.4.1 Beta

NEW FEATURES

• 36-Parameter Confound Regression Model. A new nuisance regression option has been introduced into C-PAC for confound regression using whole-brain motion parameters.

Satterthwaite TD, Elliott MA, Gerraty RT, et al. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage. 2012;64:240-56. (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811142/)

• tCompCor: Temporal Standard Deviation Noise ROI Component-Based Noise Correction. tCompCor has also been introduced into C-PAC as a nuisance regression option, for the removal of physiological noise from the functional time series.

Yashar Behzadi, Khaled Restom, Joy Liau, Thomas T. Liu. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage. 2007;37(1):90-101. (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2214855/)

• Linear anatomical registration. You can now run linear-only registration-to-template using FSL FLIRT. This allows a much faster processing time for when very high-quality nonlinear anatomical registration is not as important for your analysis.

(https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT/UserGuide)

• ndmg Mode. With ndmg-mode enabled, C-PAC runs a leaner preprocessing pipeline and produces connectome graphs using the pipeline configuration originally selected by the ndmg team and Neurodata’s pre-selected collection of atlases.

(https://neurodata.io/mri-cloud/)

IMPROVEMENTS

• Nuisance Regression Expansion. Along with the new addition of the 36-parameter motion model and tCompCor, the already-existing nuisance regression options have been expanded to include greater degrees of configurability. Refer to our updated User Guide for more details.

ERROR FIXES

• Fixed an error where C-PAC would not write outputs to an AWS S3 bucket when configured to do so.
• Fixed the "thresh_and_sum" error in the Singularity container that would cause the workflow run to fail.

COMING SOON (v1.4.2 & v1.5.0 - Spring 2019)

• Quasi-Periodic Patterns (QPP) template generation and regression
• New Group-Level Model Builder GUI
• Predictive Eye Estimation Regression (PEER)
• Non-human primate pipeline optimization
• Easy integration & analysis of other preprocessing pipeline results

C-PAC Version 1.4.0 Beta

Ease of Use

• Quick Start Guide. By pulling our Docker or Singularity container, you can kick off C-PAC with your dataset in minutes, without any prior package or library installations other than Docker or Singularity. More info available on our User Guide.
  • Find it here: http://fcp-indi.github.io/docs/user/quick.html

New Features

• Turnkey Mode. For users who prefer not to make decisions regarding their pipeline, C-PAC now includes a pre-configured default pipeline that includes the most commonly used decisions. The pre-configured pipeline selections are described in the Quick-start guide under “Running Turnkey Mode”.
• Nonparametric Permutation Inference. FMRIB’s FSL Randomise has been integrated into C-PAC’s suite of group-level analyses. You can use the already-existing FSL group-level presets or the group model builder to specify your model.

Improvements

• Early Access to the new C-PAC GUI. The first part of C-PAC’s new graphical user interface (GUI) for generating and editing custom pipelines is available! All are encouraged to take a quick test-drive of the pipeline builder and let us know your thoughts. All feedback welcome on our forum.
  • Get started: http://fcp-indi.github.io/docs/user/new_gui.html
• Group Model-Building Modularity. As part of an ongoing process of improving usability, C-PAC’s group-level analysis model builder now offers more control over your model design. It is now easier to review changes to your design matrix before specifying contrasts.
  • More info here: http://fcp-indi.github.io/docs/user/group_fsl_feat.html

Error Fixes

• An error preventing users from running only anatomical preprocessing has been fixed.
• An error in the Unpaired Two-Group Difference preset of the FSL Group Model Presets, which was causing certain covariate labels to occasionally be formatted improperly, has been fixed.

Coming Soon (Release 1.5 early 2019)

• More denoising options
• Quasi-periodic pattern (QPP) identification
• New Graphical User Interface (GUI) Upgrade
• Further modularity & usability improvements

C-PAC Version 1.3.0 Beta

Dear Colleagues,

We are happy to inform you that we have released CPAC Version 1.3.0 Beta.

New Features

1. MOVIE-FMRI ANALYSIS. Inter-Subject Correlation (ISC) and Inter-Subject Functional Connectivity (ISFC) (Simony et al., 2016). Implementation adapted from BRAINIAK.
   Dynamic reconfiguration of the default mode network during narrative comprehension. Erez Simony, Christopher J Honey, Janice Chen, Olga Lositsky, Yaara Yeshurun, Ami Wiesel & Uri Hasson. Nature Communications, 7(May 2015), 12141. (https://doi.org/10.1038/ncomms12141)
   BRAINIAK - https://github.com/brainiak/brainiak
2. GRAPH GENERATION. Users can now generate functional connectivity matrices for any parcellation set using Pearson Correlation, Partial Correlation and Tangent Embedding. Implementation based on Dadi et al (2018).
   Dadi K., Rahim M., Abraham A., Chyzhyk D., Milham M., Thirion B., Varoquaux G. (2018) Benchmarking functional connectome-based predictive models for resting-state fMRI. https://hal.inria.fr/hal-01824205
3. BOOTSTRAP-BASED FUNCTIONAL CONNECTIVITY-BASED PARCELLATION. Users can now seamlessly run Bootstrap Analysis of Stable Clusters (BASC) (Bellec et al., 2008, 2010) on data preprocessed by C-PAC. This is accomplished using PyBASC - a Python implementation of BASC, by Aki Nikolaidis - which is now integrated in C-PAC.
   Bellec, P., Marrelec, G., & Benali, H. (2008). A bootstrap test to investigate changes in brain connectivity for functional MRI. Statistica Sinica, 1253-1268.
   Bellec, P., Rosa-Neto, P., Lyttelton, O. C., Benali, H., & Evans, A. C. (2010). Multi-level bootstrap analysis of stable clusters in resting-state fMRI. Neuroimage, 51(3), 1126-1139.
   Garcia-Garcia, M., Nikolaidis, A., Bellec, P., Craddock, R. C., Cheung, B., Castellanos, F. X., & Milham, M. P. (2017). Detecting stable individual differences in the functional organization of the human basal ganglia. NeuroImage.
   https://github.com/AkiNikolaidis/PyBASC
   Nikolaidis, A., Vogelstein, J., Bellec, P., Milham, M.P. (2018). Improving Corticostriatal Parcellation Through Multilevel Bagging with PyBASC. BioRxiv.
4. ICA-AROMA. Robust de-noising using the ICA-AROMA implementation of Independent Components Analysis for the removal of motion artifacts, as implemented by Maarten Mennes.
   ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data. Pruim RHR, Mennes M, van Rooij D, Llera A, Buitelaar JK, Beckmann CF. Neuroimage. 2015 May 15;112:267-277.
   https://github.com/maartenmennes/ICA-AROMA
5. CUSTOM BRAIN EXTRACTION MASKS. You can now provide brain masks created with your own preferred skull-stripping method.

Improvements

• AWS S3 links can now be provided for all ROI and mask inputs in the pipeline configuration. This makes it easier to kick off runs without needing to gather or transfer ROI and mask files to a local disk.
• C-PAC is now compatible with Nipype version 1.1.2 (latest).

Error Fixes

• AWS S3 bucket credentials fixed to allow for anonymous connections.
• An error causing the Visual Quality Control interface to print warnings has been fixed.
• An error where the FSL FEAT Model Preset GUI dialogs would sometimes clear fields prematurely has been fixed.

Coming Soon (Releases 1.4 and 1.5 this winter)

• More ICA denoising options
• FSL Randomise
• Supervised Learning
• A new Graphical User Interface (GUI) Upgrade

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.

C-PAC Version 1.2.0 Beta

Dear Colleagues,

We are happy to inform you that we recently released CPAC Version 1.2.0 Beta. You can update your existing installations of CPAC using instructions here. Please let us know if you have any questions or feedback by posting to the forum.

New Features

• Multivariate Distance Matrix Regression (MDMR). Exploratory, connectome-wide group-level analysis that allows researchers to explore relationships between patterns of functional connectivity and phenotypic variables. Compared to traditional univariate techniques which require rigorous correction for multiple comparisons, this multivariate approach significantly reduces the number of connectivity-phenotype comparisons needed for connectome-wide associations studies. See: A multivariate distance-based analytic framework for connectome-wide association studies.

Improvements

• Improved Command-Line Interface. C-PAC is now much easier to use through the command-line interface using the "cpac" CLI tool. Users can kick off individual and group-level analyses using a nested menu, generate new pipeline and data configuration files, and set up FSL FEAT model presets, all without using the Graphical User Interface. More details available here.
• Increased Skull-Stripping Configurability. You can now modify the full range of parameters for both AFNI's 3dSkullStrip and FSL's BET for anatomical skull-stripping during preprocessing.
• Default pipeline configuration. For those who don’t want the options, C-PAC can run as a turnkey system using parameter selections recommended by our team. More details available here.
• Group-level Analysis Usability. Group-level analyses now also accept tab-separated (.tsv) files for phenotypic information. This allows users to seamlessly pull in the participants.tsv files which often accompany BIDS datasets.

Error Fixes

• An error in v1.1.0 that was causing the QC pages to crash on SNR image generation in some pipeline runs has been fixed.

Coming Soon (Release 1.3 early Fall)

• Bootstrap Analysis for Stable Clusters (BASC)
• Inter-subject Correlation (ISC)
• Independent Components Analysis (ICA)-based Denoising
• More FSL Group-Level Analysis presets
• Supervised learning

In addition, the C-PAC Docker image and AWS AMI have both been updated. These provide a quick way to get started without needing to go through the install process.

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.

CPAC Version 1.1.0 Beta

Dear Colleagues,

We are happy to inform you that we have released CPAC Version 1.1.0 Beta.

New Features

• The Visual Data Quality Control Interface is back! The QC interface provides HTML pages for each participant, scan, and preprocessing strategy featuring montage images of various preprocessing, analysis, and head motion images, graphs, and histograms. You can use these for a quick glance of your results.
• FSL FEAT Group-Level Analysis Presets. A new addition to C-PAC’s group-level analysis model builder that allows you to setup group-level models specified in the FSL User Guide with little effort. The preset generator allows you to select from a few commonly-used FEAT model configurations. The first six model types are in and more to come!
• Automated Anatomical Scan Selection (for Multisession datasets). If using a dataset that features multiple anatomical/structural scans per participant, you can now configure the data configuration builder to automatically select which anatomical file to use in your pre-processing run.

Improvements

• Leaner and Cleaner Output Directories. The layout of the output directory has been made cleaner and easier to navigate. Many of the usual outputs written to the output directory by default are now optional, saving disk space as well. There are new options in the pipeline configuration enabling you to select which additional outputs should be included in the output directory. Again, see the User Guide for more information on this change.

General Remarks

• The data configuration YAML file format has been modified to feature deeper nesting of functional-related files (such as scan parameter files or field map files). Note, data configuration files from versions prior to v1.1.0 will not work with C-PAC v1.1.0 or later - you can use any already-existing data settings YAML files to regenerate these. See the User Guide for more information, or feel free to contact us if any assistance is needed.

Error Fixes

• The z-stat output files of group-level analysis are now labeled after the contrast names provided by the user during the group model creation process.

Coming Soon (Releases 1.2 and 1.3 this summer)

• Multivariate Distance Matrix Regression (MDMR)
• Bootstrap Analysis for Stable Cluster (BASC)
• More FSL Group-Level Analysis presets
• Expanded range of skull stripping options
• Expanded nuisance regression options

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC Development Team

CPAC Version 1.0.3 Beta

Dear Colleagues,

We are happy to inform you that we recently released CPAC Version 1.0.3 Beta. You can update your existing installations of CPAC using instructions here. Please let us know if you have any questions or feedback by posting to the forum.

General Remarks

• The Subject/Participant list YAML file has been renamed the "Data Configuration" file. What used to be named the "data config", which contains the presets used to generate the participant list, has been renamed the "Data Settings" file. This also makes the main CPAC interface consistent with the CPAC BIDS-App. See the User Guide section about building a data configuration file for more information.

New Features

• Field map distortion correction via FSL FUGUE has been introduced as a pre-processing option. Users can provide the phase difference and magnitude files required to generate the field map (if applicable) through the data configuration (participant list) builder. See the User Guide section about distortion correction for more information.
• A new script called cpac_data_config_setup.py has been introduced, which allows users to quickly and easily create a data settings template for modification, and then use this data settings file to generate their data configuration. This script does the same thing that the data configuration builder GUI does, except without needing to be able to open the GUI (for example, when SSHing into a server). Information on its usage is available here.
• When building your data configuration (participant list), input data can now be filtered by site, session, and series.
• For building your data configuration (participant list), support for BIDS-protocol scan parameter reading from JSON files has been introduced.
• Logging can now be disabled by entering "run_logging: False" in your pipeline configuration YAML file.

Improvements

• The layout and naming of fields in the data configuration builder GUI are now clearer.
• More informative status messages have been introduced detailing the data configuration building process (progress, amount of input data found, etc.).
• Data configuration files (participant lists) are now ordered by site, and then participant ID, for easier searching and navigation when manually viewing or editing the YAML file.

Error Fixes

• The bug in the group-level analysis model builder GUI reported earlier, where the ordering of the contrasts in the contrast matrix provided to FSL FLAME did not always match the order in which they were specified in the group model builder GUI, has been fixed.
• An error introduced in v1.0.2 that was causing the CompCor nuisance regression strategy to not run even if it was selected in some cases, has been fixed.
• When generating a data configuration file (participant list), a bug sometimes causing some scans to not be included in a participant entry has been fixed.
• Fixed a bug where sometimes de-spiking could cause a crash if no volumes are marked for excessive motion.
• The formatting of the motion parameters CSV file has been fixed.

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.

CPAC Version 1.0.2 Beta

The updates to CPAC in this new version include:

• CPAC now offers De-Spiking as an option in nuisance regression, which regresses out the impact of motion-induced artifacts from the functional timeseries from volumes exhibiting motion greater than a specified threshold, without removing those volumes.

• Users can now select which Framewise Displacement (FD) calculation to use (Jenkinson's or Power's) when applying the motion threshold for either Scrubbing or De-Spiking.

• CPAC can now automatically select a Framewise Displacement (FD) threshold based on a percentage value provided in the pipeline configuration. For example, if provided 5%, CPAC will select a cut-off derived from the top 5% of highest-motion volumes. See the User Guide for more information.

• Scrubbing has been moved to the Nuisance Regression tab in the GUI's pipeline configuration editor. The pipeline configuration YAML keys have changed for scrubbing settings. See the User Guide Nuisance Regression page and the sample pipeline configuration file for more details.

• Re-introduced the ability to stop pipeline runs easily from the GUI.

• Fixed a bug in the data configuration (subject list) builder that would cause non-NIfTI files to be included if the user did not explicitly define the file extension in the file template.

• Fixed a bug in the data configuration (subject list) builder where some fields would not get populated when re-loading the settings in the GUI.

• Added better error-catching and messages in nuisance regression which warn the user if nuisance parameters are too stringent for the regression to complete properly.

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.

CPAC Version 1.0.1b Beta

The updates to CPAC in this new version include:

• CPAC is now compatible with Nipype version 0.13.
• AWS S3 bucket support for BIDS data format participant list builder.
• The pipeline configuration editor’s “Test Configuration” feature now works with participant lists that contain AWS S3 paths.
• The cpac_install.sh and cpac_setup.py scripts have been fixed to be compatible with recent changes.
• Fixed a bug in the group-level analysis model builder that would prevent the user from running group analysis on outputs from Seed-Based Correlation Analysis.
• Fixed a bug in the group-level analysis pipeline where AFNI 3ddot would fail when performing a check on the merged 4D derivative file.
• Fixed an issue where crash files would be generated at the beginning of the pipeline for the ‘check_for_s3’ nodes even when not pulling data from an S3 bucket.
• Added more checks for file permissions and scan names at the beginning of the pipeline run.

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.

CPAC Version 1.0.1 Beta

The updates to CPAC in this new version include:

• Nipype and CPAC have been updated to use a resource aware scheduler that incorporates information about the amount of memory and cores currently available when choosing a pipeline step to run. This should maximize running different pipeline steps in parallel while reducing the occurrence of out-of-memory errors and system lock-ups.
• CPAC now calculates network centrality derivatives using the new 3dDegreeCentrality, 3dECM, and 3dLFCD AFNI tools implemented by our developers. These implementations are optimized to minimize the memory requirements while speeding up computation time. If you have an already-existing installation of AFNI that does not have these newer tools, you can update your installation by running "@update.afni.binaries" from your AFNI installation directory.
• Group-level analysis has been over-hauled to make it run more quickly, handle repeated measures, make entering contrasts more intuitive, and improve transparency in to the model generation process.
• The BIDS data format is now supported and the participant list builder can generate a participant list given a BIDS base directory.
• CPAC inputs can now be directly downloaded from (and outputs can be directly uploaded to) AWS S3 cloud storage.
• For the subject list generated, we replaced the confusing "%s" identifiers in file path templates with {participant}, {site}, {session} to make generating these templates more user friendly. These identifiers are also more flexible, allowing you to combine them with substrings or include multiples, allowing for greater freedom in custom input data directory formats.
• The GUI has been reorganized to simplify pipeline configuration, and specifically to improve handling of nuisance correction strategies and specifying ROIs for time series extraction and seed correlation analysis.
• SLURM cluster resource scheduler compatibility added.
• The output resolution in MNI space for statistical derivatives (e.g., ReHo, DC, etc) and 4D preprocessed functional data can be specified separately. The user can now also decide not to write the 4D preprocessed data into MNI space. Both of these steps can significantly reduce memory and disk space requirements.
• Functional nuisance regressors data now included in the output.

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.

CPAC Version 1.0.1 Beta

The updates to CPAC in this new version include:

Participant list builder fixes:

• The {participant}, {session}, etc. tags once again work properly, and are now more flexible for custom filepath formats. For example, multiple tags on one directory level, combinations of tags and custom string prefixes/suffixes, and multiple instances of the same tag in one path template are now all supported.
• When providing a participant inclusion list (under Subjects to Include) and a site inclusion list (under Sites to Include) at the same time, the builder used to ignore the Sites to Include input. This is no longer the case and will generate an intersection of the Sites and Participant inclusion lists provided.
• Including a scan parameters CSV containing information for multiple sites during participant list generation will no longer include scan parameters for sites not included in your data.
• Addition of informative messages while constructing the participant list- will warn the user when a participant included in Subjects to Include does not exist or could not be found in the data, and will list these missing participant IDs.
• When the input data does not have a session level, the participant list builder will now provide the default session "ses-1" instead of requiring a session level to be included. This is the case for both BIDS and custom data formats.

Installation script updates:

• Now more robust to package name differences between different versions of Ubuntu.
• Now uses the Neurodebian ants package for all versions of Ubuntu except for 14.04.
• Compiles libxp for Ubuntu >= 16.04 for AFNI.

Other updates:

• The nuisance regressors are now written out to a 1D file found under "functional_nuisance_regressors" in the output directory.
• Fixed a bug where locally-stored input files would potentially deleted if the user would use the "Test Configuration" feature with a participant list that contained both S3 links and local filepath file templates.
• A few redundant and unnecessary directories in the individual-level analysis output directory have been removed. These were re-writes of the ANTS-based anatomical registration warp files.
• The pipeline configuration file editor now includes the CPAC version number in the configuration YAML file.
• More informative error messages for when there is a problem in the pipeline configuration, such as the presence of unreferenced variable names in file paths.

Updated user documentation for this release can be found here:
http://fcp-indi.github.io/docs/user/index.html

And as always, you can contact us here for user support and discussion:
https://groups.google.com/forum/#!forum/cpax_forum

Regards,
The CPAC development team.