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@INPROCEEDINGS{Jockwitz:1048935,
      author       = {Jockwitz, Christiane and Mendl-Heinisch, Camilla and
                      Miller, Tatiana and Dellani, Paulo R. and Caspers, Svenja},
      title        = {{P}rediction of individual cognitive test scores from brain
                      and non-brain data across the adult lifespan},
      reportid     = {FZJ-2025-05032},
      year         = {2025},
      abstract     = {Predicting cognitive decline in aging remains a challenging
                      but important topic. Existing results are heterogeneous,
                      potentially due to the non-linear nature of both, cognitive
                      decline and the factors that influence it. We here aimed to
                      systematically examine the predictability of cognitive
                      abilities based on brain and non-brain data across five
                      decades of the adult lifespan in the large German National
                      Cohort (NAKO; N = 23,863; 25 to 75 years). Brain summary
                      statistics (e.g. total grey matter), health (e.g.
                      body-mass-index) and demographic (i.e. age, sex, education)
                      data were used to predict four cognitive scores using a
                      machine learning (ML; repeated nested cross-validation; four
                      regression algorithms) approach.Current results emphasize
                      that demographics tend to outperform brain and health
                      factors in predicting cognitive abilities in a large sample
                      spanning the whole adulthood, with better predictability for
                      episodic memory and interference compared to verbal fluency
                      and working memory. Contrary to the hypothesis of a worse
                      prediction at older ages, prediction appeared to be
                      similarly low in each decade. Hence, sample size seems to
                      matter even more than sample homogeneity. Including a wide
                      age range for reaching large sample sizes, though, could
                      come at the cost of predicting a hidden age effect.},
      month         = {May},
      date          = {2025-05-07},
      organization  = {Aging and Cognition Conference, Pavia
                       (Italy), 7 May 2025 - 10 May 2025},
      subtyp        = {After Call},
      cin          = {INM-1},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / HBP SGA3 - Human Brain Project Specific Grant
                      Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/1048935},
}