Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics

Luppi, Andrea I., Gellersen, Helena M., Liu, Zhen-Qi, Peattie, Alexander R. D., Manktelow, Anne E., Adapa, Ram, Owen, Adrian M., Naci, Lorina, Menon, David K., Dimitriadis, Stavros I. ORCID: https://orcid.org/0000-0002-0000-5392 and Stamatakis, Emmanuel A. 2024. Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics. Nature Communications 15 (1) , 4745. 10.1038/s41467-024-48781-5

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Abstract

Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines’ suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline’s performance across criteria and datasets, to inform future best practices in functional connectomics.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Psychology Cardiff University Brain Research Imaging Centre (CUBRIC) MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/, Type: open-access
Publisher:	Nature Research
ISSN:	2041-1723
Date of First Compliant Deposit:	5 June 2024
Date of Acceptance:	10 May 2024
Last Modified:	05 Jun 2024 09:15
URI:	https://orca.cardiff.ac.uk/id/eprint/169484

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