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Harnessing reliability for neuroscience research

Author

Listed:
  • Xi-Nian Zuo

    (University of Chinese Academy of Sciences (UCAS)
    Nanning Normal University
    South China Normal University
    CAS Institute of Psychology)

  • Ting Xu

    (CAS Institute of Psychology
    Child Mind Institute)

  • Michael Peter Milham

    (Child Mind Institute
    Nathan S. Kline Institute for Psychiatric Research)

Abstract

Neuroscientists are amassing the large-scale datasets needed to study individual differences and identify biomarkers. However, measurement reliability within individual samples is often suboptimal, thereby requiring unnecessarily large samples. We focus our comment on reliability in neuroimaging and provide examples of how the reliability can be increased.

Suggested Citation

  • Xi-Nian Zuo & Ting Xu & Michael Peter Milham, 2019. "Harnessing reliability for neuroscience research," Nature Human Behaviour, Nature, vol. 3(8), pages 768-771, August.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:8:d:10.1038_s41562-019-0655-x
    DOI: 10.1038/s41562-019-0655-x
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    Cited by:

    1. Eric W Bridgeford & Shangsi Wang & Zeyi Wang & Ting Xu & Cameron Craddock & Jayanta Dey & Gregory Kiar & William Gray-Roncal & Carlo Colantuoni & Christopher Douville & Stephanie Noble & Carey E Prieb, 2021. "Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics," PLOS Computational Biology, Public Library of Science, vol. 17(9), pages 1-20, September.
    2. Loïc Labache & Tian Ge & B. T. Thomas Yeo & Avram J. Holmes, 2023. "Language network lateralization is reflected throughout the macroscale functional organization of cortex," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Guan, Sihai & Wan, Dongyu & Yang, Yanmiao & Biswal, Bharat, 2022. "Sources of multifractality of the brain rs-fMRI signal," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Joana Barroso & Kenta Wakaizumi & Diane Reckziegel & João Pinto-Ramos & Thomas Schnitzer & Vasco Galhardo & A Vania Apkarian, 2020. "Prognostics for pain in osteoarthritis: Do clinical measures predict pain after total joint replacement?," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-22, January.

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