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@PHDTHESIS{Heckner:1038288,
      author       = {Heckner, Marisa},
      title        = {{P}rediction of {C}ognitive {F}unctioning across the
                      {L}ifespan {U}sing {S}tructural and {F}unctional
                      {N}euroimaging {D}ata},
      school       = {Heinrich-Heine-Universität Düsseldorf},
      type         = {Dissertation},
      reportid     = {FZJ-2025-01299},
      pages        = {63},
      year         = {2024},
      note         = {Dissertation, Heinrich-Heine-Universität Düsseldorf,
                      2024},
      abstract     = {Healthy aging is associated with structural and functional
                      changes in the brain. These changes areespecially pronounced
                      in complex cognitive tasks, like executive functioning (EF).
                      EF is importantfor decision-making, problem-solving, and
                      adaptive behavior. Advances in neuroimaging techniqueshave
                      enabled a more detailed exploration of the neural substrates
                      of cognitive aging, yet theneural underpinnings of EF,
                      especially in the context of cognitive aging, remain
                      incompletely understood.The global demographic shift towards
                      an older population underscores the importance
                      ofunderstanding cognitive aging, particularly changes in
                      EF.This dissertation aimed to investigate the structural and
                      functional neural substrates and dynamicsof age-related
                      differences in EF through a comprehensive methodological
                      framework combiningmeta-analyses, functional connectivity
                      analyses, and predictive modeling.Meta-analyses highlighted
                      left inferior frontal junction and left anterior
                      cuneus/precuneus as regionssignificantly affected by aging,
                      with recruitment patterns varying by task type and age.
                      Subsequently,a meta-analytic synthesis identified a common
                      perceptuo-motor network, comprisingvisual, auditory, and
                      motor-related brain regions. This allows for the
                      investigation of age differencesalready at the in- and
                      output levels of the brain, which in turn could influence
                      performanceat higher cognitive levels. Prediction studies
                      revealed moderate to low overall prediction accuracies,with
                      measures of functional within-subject variability showing
                      superior predictive performancefor younger and structural
                      measures for older adults. Surprisingly, whole-brain and
                      randomnetwork approaches outperformed EF-specific networks
                      in predicting EF abilities, suggesting thatbroader network
                      properties may be more indicative of individual differences
                      in EF than previouslythought.The findings highlight the
                      complex interplay between structural and functional brain
                      changes andcognitive aging, emphasizing an age-dependent
                      modality specificity in the neural predictors of
                      EFperformance. The differential effectiveness of global
                      versus EF-specific networks in predicting EFunderscores the
                      potential value of considering global brain characteristics
                      and combining multiplemetrics to enhance predictive
                      accuracy. The modest to low prediction accuracies call for
                      furtherresearch into developing more effective biomarkers
                      for EF abilities, considering broader networkdynamics, and
                      adopting adaptive behavioral testing approaches to capture
                      the full performancespectrum of healthy aging.},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / 5253 - Neuroimaging (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(DE-HGF)POF4-5253},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.34734/FZJ-2025-01299},
      url          = {https://juser.fz-juelich.de/record/1038288},
}