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Moving beyond processing- and analysis-related variation in resting-state functional brain imaging.

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Affiliations

  • 1. Child Mind Institute, New York, NY, USA.
      Authors
    • Li X 1
    • Bianchini Esper N 1
    • Ai L 1
    • Giavasis S 1
    • Jin H 1
    • Xu T 1
    • Clucas J 1
    • Franco A 1
    • Kiar G 1
    • Milham MP 1
    (10 authors)
  • 2. Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
      Authors
    • Feczko E 2
    • Fair D 2
    (2 authors)
  • 3. Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX, USA.
      Authors
    • Sólon Heinsfeld A 3
    • Craddock C 3
    (2 authors)
  • 4. Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
      Authors
    • Adebimpe A 4
    • Satterthwaite T 4
    (2 authors)
  • 5. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
      Authors
    • Vogelstein JT 5
    (1 author)
    • Show all (8)

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Nature Human Behaviour, 05 Aug 2024, 8(10):2003-2017
https://doi.org/10.1038/s41562-024-01942-4 PMID: 39103610 

Abstract 

When fields lack consensus standard methods and accessible ground truths, reproducibility can be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools and processing pipelines. We provide a critical evaluation of the impact of differences across five independently developed minimal preprocessing pipelines for functional magnetic resonance imaging. We show that, even when handling identical data, interpipeline agreement was only moderate, critically shedding light on a factor that limits cross-study reproducibility. We show that low interpipeline agreement can go unrecognized until the reliability of the underlying data is high, which is increasingly the case as the field progresses. Crucially we show that, when interpipeline agreement is compromised, so too is the consistency of insights from brain-wide association studies. We highlight the importance of comparing analytic configurations, because both widely discussed and commonly overlooked decisions can lead to marked variation.

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Read article at publisher's site: https://doi.org/10.1038/s41562-024-01942-4

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Funding 

Funders who supported this work.

NIMH NIH HHS (1)

National Natural Science Foundation of China (3)

National Natural Science Foundation of China (National Science Foundation of China) (3)

U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) (4)

U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (4)