CONN

functional connectivity toolbox

over 50,000 downloads, continuous software development and yearly releases since 2010

@ nitrc.org/projects/conn

over 3,000 articles published using CONN for functional connectivity and resting state analyses

@ google scholar

over 10,000 forum posts and 3,000 topic threads offering support to CONN users

@ nitrc.org/projects/conn

Latest news :

December 2020: check out the latest CONN release (20b) @ NITRC

CONN's 2020 releases brought several usability improvements, such as the ability to define group-level analyses using simple QDEC-style questions, a simplified 1st-level analysis GUI, and a streamlined fMRIPrep import process, as well as several brand new analysis tools, including a novel Threshold Free Cluster Enhancement implementation, and new cluster-based inferences for ROI-to-ROI connectivity matrices

Software description

CONN is an open-source Matlab/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:

    • Importing DICOM, ANALYZE, and NIfTI functional and anatomical files, either raw or partially/fully preprocessed volumes. Automatic import tools for BIDS datasets and fMRIPrep outputs

    • Standardized preprocessing pipelines of functional and anatomical volumes powered by SPM12 (including susceptibility distortion correction, motion correction / realignment, slice-timing correction, outlier identification, coregistration, tissue-class segmentation, MNI-normalization, and smoothing)

    • Control of residual physiological and motion artifacts (e.g. scrubbing, aCompCor, ICA-based denoising, Global Regression, band-pass filtering)

    • Integrated quality control procedures and measures (e.g. FC histogram plots, BOLD signal carpetplots, Framewise Displacement, GCOR measures, FC-QC correlations)

    • Multiple connectivity analyses and measures, including Seed-Based Correlations (SBC), ROI-to-ROI analyses, complex-network analyses, generalized Psycho-Physiological Interaction models (gPPI), Independent Component Analyses (group-ICA), masked ICA, Amplitude of Low-Frequency Fluctuations (ALFF & fALFF), Intrinsic Connectivity (ICC), Local Homogeneity (LCOR), Global Correlations (GCOR), Multivoxel Pattern Analyses (MVPA), and dynamic connectivity analyses (dyn-ICA, sliding-window correlations)

    • Group- and population-level inferences and models, including ANOVA, regression, longitudinal, experimental, and mixed within- and between-subject designs. Univariate and Multivariate statistics. Control for multiple comparisons using parametric (e.g. Random Field Theory), and non-parametric permutation/randomization techniques (e.g. Threshold Free Cluster Enhancement)

When used within a distributed cluster or multi-processor environment CONN can automatically parallelize most time consuming steps in the fcMRI processing pipeline, allowing the analyses of hundreds of subjects in minimal time. CONN can be entirely controlled through a user-friendly GUI, or through batch scripts/commands if preferred.

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 this section for a detailed description of all processing and analysis methods available in CONN

Citing CONN

To cite CONN in your work please include one or several of the following references:

For details about CONN's processing pipeline and analysis methods: