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Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics
- Source :
- Nature Communications, Vol 15, Iss 1, Pp 1-24 (2024)
- Publication Year :
- 2024
- Publisher :
- Nature Portfolio, 2024.
-
Abstract
- 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.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 15
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3735640386ca4b8499907e042d93176d
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-024-48781-5