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@ARTICLE{Gell:1034337,
      author       = {Gell, Martin and Eickhoff, Simon B. and Omidvarnia, Amir
                      and Küppers, Vincent and Patil, Kaustubh R. and
                      Satterthwaite, Theodore D. and Müller, Veronika I. and
                      Langner, Robert},
      title        = {{H}ow measurement noise limits the accuracy of
                      brain-behaviour predictions},
      journal      = {Nature Communications},
      volume       = {15},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Nature Publishing Group UK},
      reportid     = {FZJ-2024-07122},
      pages        = {10678},
      year         = {2024},
      abstract     = {Major efforts in human neuroimaging strive to understand
                      individual differences and find biomarkers for clinical
                      applications by predicting behavioural phenotypes from brain
                      imaging data. To identify generalisable and replicable
                      brain-behaviour prediction models, sufficient measurement
                      reliability is essential. However, the selection of
                      prediction targets is predominantly guided by scientific
                      interest or data availability rather than psychometric
                      considerations. Here, we demonstrate the impact of low
                      reliability in behavioural phenotypes on out-of-sample
                      prediction performance. Using simulated and empirical data
                      from four large-scale datasets, we find that reliability
                      levels common across many phenotypes can markedly limit the
                      ability to link brain and behaviour. Next, using 5000
                      participants from the UK Biobank, we show that only highly
                      reliable data can fully benefit from increasing sample sizes
                      from hundreds to thousands of participants. Our findings
                      highlight the importance of measurement reliability for
                      identifying meaningful brain–behaviour associations from
                      individual differences and underscore the need for greater
                      emphasis on psychometrics in future research.},
      cin          = {INM-7 / IET-1},
      ddc          = {500},
      cid          = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)IET-1-20110218},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5254},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {39668158},
      UT           = {WOS:001377360000005},
      doi          = {10.1038/s41467-024-54022-6},
      url          = {https://juser.fz-juelich.de/record/1034337},
}