CONN
functional connectivity toolbox
# academic publications to date using CONN for functional connectivity analyses
@ google scholar
SOFTWARE DESCRIPTION
CONN is an OPEN-SOURCE SPM-based cross-platform software for the computation, display, and analysis of functional connectivity Magnetic Resonance Imaging (fcMRI). CONN is used to analyze resting state data (rsfMRI) as well as task-related designs. Processing and analysis steps in CONN include:
Options to automatically import datasets in standardized formats (e.g. BIDS, fMRIPrep) and to download publicly available datasets directly into CONN (e.g. FCP/INDI). Flexible options to import raw data (e.g. DICOM, ANALYZE, NIfTI) or data partially or fully preprocessed using other tools (e.g. SPM, FSL, AFNI).
Standardized preprocessing pipelines of functional and anatomical volumes powered by SPM (including susceptibility distortion correction, motion correction / realignment, slice-timing correction, outlier identification, coregistration, tissue-class segmentation, MNI-normalization, smoothing)
Strict control of residual physiological and subject motion artifacts (denoising methods include scrubbing, motion regression, anatomical CompCor, band-pass filtering)
Integrated quality control procedures and measures (e.g. FC histogram plots, BOLD signal carpetplots, FC-QC correlation displays)
Multiple connectivity analyses and measures, including Seed-Based Correlations (SBC), ROI-to-ROI connectivity (RRC), graph theoretical analyses, generalized Psycho-Physiological Interaction models (gPPI), Independent Component Analyses (group-ICA), masked ICA, Amplitude of Low-Frequency Fluctuations (ALFF), Intrinsic Connectivity (ICC & GCOR), Local Correlations (LCOR), Inter-Hemispheric Correlations (IHC), functional connectivity Multivariate Pattern Analyses (fc-MVPA), and dynamic connectivity analyses (dyn-ICA, and sliding-window analyses)
Group- and population-level inferences and models, including ANOVA, regression, repeated measures and mixed within- and between-subject designs. Univariate and Multivariate statistics. False positive control using parametric (e.g. Random Field Theory) and non-parametric techniques (e.g. permutation/randomization analyses, Threshold Free Cluster Enhancement)
CONN can be entirely controlled using a user-friendly GUI, or using batch scripts/commands. When used within a high-performance computing (HPC) environment CONN is able to interact automatically with most workload manager protocols (e.g. Slurm, Grid Engine, PBS/Torque, LSF) allowing CONN to process thousands of subjects in parallel with minimal user interaction.
The toolbox is developed in Matlab, and it is distributed both as Matlab source code and as a pre-compiled executable file (standalone release, no Matlab installations or licenses required).
See the fMRI methods section for a detailed description of all processing and analysis methods available in CONN.
SOFTWARE LICENSE
CONN software is distributed free of charge under a MIT license, granting permission to all CONN users to use this software without restriction.
If you find this software useful for your research, please consider supporting CONN:
If you or your institution have funds allocated for training, consider signing up to one of our training courses to help you master CONN and keep up to date with all of its functionality (all proceeds from these courses are directed towards the continuous development of CONN).
Visit CONN's GitHub site and help develop, test, or document the CONN software.
Share your knowledge about functional connectivity and CONN by visiting CONN's NITRC forum and answering questions from other CONN users, or simply help us spread the word and let those around you learn about CONN from your own experience!
LATEST NEWS
September 2024. Announcing the next CONN workshops
CONN workshops offer 35 hours of intensive hands-on and highly interactive classes covering all aspects of functional connectivity analyses in CONN. The next workshop will take place in-person (in Boston) between Nov 11 and Nov 15 2024. After that, the following CONN workshop will take place online (via ZOOM meetings) between Jan 17 and Feb 17 2025.
July 2024. Check out the latest release of the CONN toolbox (v2407)
This release includes all existing patch updates (enabling for example the use of CONN natively on newer "Apple-silicon" Mac computers) as well as many upgrades to CONN's analysis and plotting functions (see the change log for a full list of changes). For example, one new functionality that we are particularly excited about is the ability in CONN to create a new project and automatically populate it with data from FCP (1000 Functional Connectomes Project), including resting state scans from over 1,200 subjects. We are hoping to continue integrating other public datasets in the future if this feature is found to be useful by CONN users, so please give it a try and send us any feedback, comments, or suggestions.
March 2023. The latest release of the CONN toolbox (CONN 22a) is out
This release brings many exciting updates, including new options for fc-MVPA analyses and an interactive GUI exploring the entire brain-wide functional connectome (similar to AFNI InstaCorr but combining all subjects in a study; see 2nd-level fc-MVPA summary tab), new automated "Methods" descriptions to help describe CONN's processing and analysis steps in your manuscripts, and several new displays options (e.g. 'connections display' and 'glass display' in ROI-to-ROI, or 'network display' in voxel-level results explorer windows), among many others. See the release changes log and the updated manual for details.
using the new fc-MVPA data visualization tool: can you spot some of the classical networks (e.g. DMN, salience / VAN, frontoparietal / CEN) in these voxel-to-voxel maps?
February 2023. CONN can now help you write the Methods section of your manuscript by creating automatically boilerplate text describing the specific procedures and methods used by CONN in your project.
Many replicability efforts stumble at the initial steps by a lack of rigorous reporting of the specific choices used by a team when processing and analyzing their data. To help change this, CONN can now create boilerplate descriptions of the specific preprocessing, denoising, and analysis choices that were used in your CONN project. These automatic descriptions are distributed under a public domain license and can be used, copied, modified and redistributed freely as part of the Methods section of your manuscript, or anywhere else. See this section for additional details.
This is a work in progress and we welcome your feedback to help us make these descriptions as informative and useful as possible!
Methods.pdfNovember 2022. Check out some of the latest functional connectivity analysis methods available in CONN : Nieto-Castanon, A. (2022). Brain-wide connectome inferences using functional connectivity MultiVariate Pattern Analyses (fc- MVPA). PLoS Comput Biol 18(11): e1010634
Fc-MVPA analyses allow researchers to test hypotheses about the entire functional connectome (all voxel-to-voxel functional connections across the entire brain), without having to limit the analyses to a single or a few seed areas (e.g. SBC analyses) or a specific parcellation of the brain into ROIs (e.g. RRC analyses). For example, questions like "is functional connectivity different between patients and control subjects?", "does functional connectivity change with an intervention?", or "what aspects of functional connectivity covary with symptom severity?" can be asked using fc-MVPA examining the entire set of (billions of) functional connections between all pairs of individual voxels in the fMRI images.
