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Structural and functional connectivity reconstruction with CATO - A Connectivity Analysis TOolbox.

Siemon C de Lange1, Koen Helwegen2, Martijn P van den Heuvel3

  • 1Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands.

Neuroimage
|April 14, 2023
PubMed
Summary
This summary is machine-generated.

We introduce the Connectivity Analysis TOolbox (CATO), a software for reconstructing brain connectivity from MRI data. CATO enables end-to-end analysis for structural and functional connectomes, aiding neuroimaging research.

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Informatics

Background:

  • Brain connectivity analysis is crucial for understanding brain function and disorders.
  • Existing tools may lack multimodal integration or user customization for complex analyses.
  • Reconstructing accurate structural and functional connectomes requires robust and flexible software solutions.

Purpose of the Study:

  • To introduce the Connectivity Analysis TOolbox (CATO), a novel multimodal software package.
  • To enable end-to-end reconstruction of structural and functional brain connectivity from MRI data.
  • To provide researchers with a customizable platform for advanced connectome mapping.

Main Methods:

  • CATO integrates diffusion-weighted imaging (DWI) and resting-state functional MRI (rs-fMRI) data processing.
  • It supports user-defined (sub)cortical atlases for aligned connectivity matrix generation.
  • Pipelines were validated using simulated DWI data (ITC2015) and Human Connectome Project (HCP) datasets.

Main Results:

  • CATO facilitates the reconstruction of structural and functional connectome maps.
  • The toolbox allows for customized analysis pipelines and integration of various preprocessing packages.
  • Performance validation confirmed the reliability of CATO with benchmark datasets.

Conclusions:

  • CATO offers a comprehensive and flexible solution for multimodal brain connectivity analysis.
  • The open-source nature and availability as a MATLAB toolbox or stand-alone application enhance accessibility.
  • CATO empowers researchers to conduct integrative analyses of brain structure and function.