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@INPROCEEDINGS{Weis:863320,
      author       = {Weis, Susanne and Patil, Kaustubh and Hoffstaedter, Felix
                      and Eickhoff, Simon},
      title        = {{A}ge effects on sex classification performance},
      reportid     = {FZJ-2019-03400},
      year         = {2019},
      abstract     = {Cognitive sex differences have repeatedly been examined
                      both in behaviour and task-related functional magnetic
                      resonance imaging (fMRI). More recently, machine-learning
                      approaches have successfully been employed to predict the
                      sex of a person from whole brain and regionally specific
                      resting state (RS) functional brain connectivity patterns.
                      Differentiating patterns of brain connectivity between the
                      sexes are presumably based on biological factors as well as
                      social influences and experiences ([2]). Thus, sex
                      differences in brain connectivity might be modulated by age.
                      The present study aimed to examine if brain regions that
                      most reliably distinguish between males and females differ
                      between younger and older participants. The RS connectome
                      was extracted from fMRI data in a sub-sample of the enhanced
                      Nathan Kline Institute-Rockland Sample (NKI-RS; [1]), in
                      which males and females were matched for age (n = 380, 190
                      males, age range: 8 – 83). For each of 436 regions (ROIs),
                      connectivity patterns were defined by the Pearson
                      correlations between each ROI’s time course and the rest
                      of the brain, which were then transformed to Fischer’s
                      Z-scores. Regional connectivity patterns were used as
                      features in a sex classification analysis, employing a
                      non-linear support vector machine (SVM) approach that was
                      conducted individually for each ROI. Excluding the median
                      age range of 25 – 35, classification accuracies for each
                      ROI were assessed separately for the young (n=166) and the
                      old (n=168) part of the sample. For both groups,
                      classification accuracies (Acc) were above chance for all
                      ROIs across the brain (young: min Acc = $67.11\%,$ old: min
                      Acc = $60.71\%).$ Across the whole brain, accuracies were
                      significantly higher for the young (mean Acc: $74.21\%;$ SD:
                      $2.56\%)$ then for the old group (mean Acc: $68.54\%;$ SD:
                      $2.91\%;$ t = 36.78; p < 0.001). Regions displaying
                      significantly higher sex classification accuracies for the
                      young then for the old group ( χ2(1) > 4.73, p < 0.05) were
                      located in the left inferior, middle, medial and orbital
                      frontal gyrus, the right middle, superior and orbital
                      frontal gyrus, left pre- and postcentral gyrus, as well as
                      bilateral palladium and putamen. Functional decoding
                      associated these areas with language functions, reward,
                      memory, task-switching and inhibition. Our data show that
                      regional RS brain connectivity can be used to reliably
                      predict sex both in younger and older subjects. Lower
                      accuracies in the older group indicate that brain
                      connectivity patterns become less sex-specific in older as
                      opposed to younger subjects. Most pronounced lower
                      accuracies in lateral and medial frontal cortices indicate
                      that frontal brain connectivity becomes more similar in
                      older males and females. As the frontal cortex has often
                      been associated with monitoring and control of behaviour and
                      cognitive strategies, these findings might indicate that
                      with aging, frontal cortex modulatory influences on other
                      brain regions becomes more similar between the sexes,
                      supporting compensatory sex-dependent processes that act to
                      reduce cognitive sex differences ([3])[1] Nooner KB et al.
                      Frontiers in neuroscience (2012) 6:152.[2] Jancke L.
                      F1000Res (2018) 7.[3] de Vries GJ $\&$ Sodersten P. Horm
                      Behav (2009) 55(5):589-596.},
      month         = {Jan},
      date          = {2019-01-25},
      organization  = {2019 European Workshop on Cognitive
                       Neuropsychology, Bressanone (Italy), 25
                       Jan 2019 - 25 Jan 2019},
      subtyp        = {Other},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571)},
      pid          = {G:(DE-HGF)POF3-571},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/863320},
}