Personode: A Toolbox for ICA Map Classification and Individualized ROI Definition

Abstract

Canonical resting state networks (RSNs) can be obtained through independent component analysis (ICA). RSNs are reproducible across subjects but also present inter-individual differences, which can be used to individualize regions-of-interest (ROI) definition, thus making fMRI analyses more accurate. Unfortunately, no automatic tool for defining subject-specific ROIs exists, making the classification of ICAs as representatives of RSN time-consuming and largely dependent on visual inspection. Here, we present Personode, a user-friendly and open source MATLAB-based toolbox that semi-automatically performs the classification of RSN and allows for defining subject- and group-specific ROIs. To validate the applicability of our new approach and to assess potential improvements compared to previous approaches, we applied Personode to both task-related activation and resting-state data. Our analyses show that for task-related activation analyses, subject-specific spherical ROIs defined with Personode produced higher activity contrasts compared to ROIs derived from single-study and meta-analytic coordinates. We also show that subject-specific irregular ROIs defined with Personode improved ROI-to-ROI functional connectivity analyses.

Hence, Personode might be a useful toolbox for ICA map classification into RSNs and group- as well as subject-specific ROI definitions, leading to improved analyses of task-related activation and functional connectivity.

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Acknowledgements

This work was supported by the Brazilian National Council for Scientific and Technological Development (CNPq), the Brazilian National Council for the Improvement of Higher Education (CAPES), the Swiss National Science Foundation (BSSG10_155915, 100014_178841, 32003B_166566), the Foundation for Research in Science and the Humanities at the University of Zurich (STWF-17-012), the Baugarten Stiftung, and the Swiss Government. We also thank Dr. Ludovica Griffanti for insightful discussions and comments on the manuscript.

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Correspondence to Gustavo S. P. Pamplona.

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Information Sharing Statement

NKI/Rockland Sample (RRID:SCR_009435) data used in this work is available at https://fcon_1000.projects.nitrc.org/indi/enhanced/neurodata.html. UK Biobank (RRID:SCR_012815) group-averaged RSNs templates where obtained at http://biobank.ctsu.ox.ac.uk/showcase/refer.cgi?id=9028.

SPM12 (RRID:SCR_007037,https://www.fil.ion.ucl.ac.uk/spm/software/spm12/), MarsBaR (RRID:SCR_009605,http://marsbar.sourceforge.net), and GIFT (RRID:SCR_001953,http://trendscenter.org/trends/software/gift/) are available to the general public.

The source code of Personode is available free of charge for non-commercial use and adaptation, under the condition of proper attribution, at https://github.com/gustavopamplona/Personode.

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Pamplona, G.S.P., Vieira, B.H., Scharnowski, F. et al. Personode: A Toolbox for ICA Map Classification and Individualized ROI Definition. Neuroinform 18, 339–349 (2020). https://doi.org/10.1007/s12021-019-09449-4

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Keywords

  • ROI individualization
  • ICA map classification
  • Resting-state networks
  • Toolbox
  • Independent component analysis
  • Functional connectivity