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@INPROCEEDINGS{Nicolaisen:903648,
      author       = {Nicolaisen, Eliana and Kharabian, Shahrzad and Mihalik,
                      Agoston and Ferreira, Fabio and Maleki Balajoo, Somayeh and
                      Eickhoff, Simon and Thomas Yeo, B. T. and Mourao-Miranda,
                      Janaina and GENON, Sarah and Valk, Sofie},
      title        = {{H}eritable and robust latent dimension linking cognition
                      and multi-featured brain structure in healthy adults},
      reportid     = {FZJ-2021-05297},
      year         = {2021},
      abstract     = {Multivariate methods are promoted to study solid
                      brain-behaviour relationships1,2. Canonical Correlation
                      Analysis (CCA) has been used to analyse latent dimensions of
                      brain-behaviour interindividual variability3–5⁠.
                      However, more robust results can be found with regularised
                      CCA (RCCA) and assessing generalizability (model performance
                      in new data) and stability (if different data splits yield
                      similar results)6,7⁠. In addition, the heritability of
                      these dimensions would help understand their genetic load.We
                      studied robust brain-behaviour latent dimensions (Human
                      Connectome Project; n: 1047, mean age: 28.78; 560 females).
                      Brain structure included region-wise Grey Matter Volume
                      (GMV; CAT12), Cortical Thickness and Surface Area (CT and SA
                      respectively; FreeSurfer v5.3). Behavioural data spanned
                      cognition, emotion and mental health. We used RCCA and a
                      novel machine learning framework to optimise
                      generalisability and stability6,7⁠. We also studied the
                      heritability of the latent dimension.We found one
                      significant latent dimension (r=0.46-0.32, p=0.04)
                      positively associated with
                      cognitive-control/executive-functions. CT loadings were
                      negative in associative areas and positive in sensoriomotor
                      areas. SA and GMV loadings were positive on the temporal
                      pole, inferior temporal gyri, pars orbitalis, anterior
                      cingulate cortex and postcentral gyri. GMV loadings were
                      negative in cerebellum and basal ganglia. Heritability of
                      brain (h2=0.85) and behavioural scores (h2=0.82) and their
                      genetic correlation (rhog=0.66) were significant
                      (p<0.000).The dimension found captured variability from
                      higher to lower cognitive-control/executive-functions.
                      Accordingly, brain loadings ranged from lower to higher
                      regions of the brain cortex and were similar to the pattern
                      of cortical expansion during evolution and human
                      development. The brain and behavioural scores were found to
                      be heritable and to have shared genetic factors. Better
                      characterizing these dimensions should help to prevent
                      pathological extremes.},
      month         = {Oct},
      date          = {2021-10-05},
      organization  = {INM $\&$ IBI Retreat, Virtual
                       (Germany), 5 Oct 2021 - 6 Oct 2021},
      subtyp        = {After Call},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5253 - Neuroimaging (POF4-525) / 5251 - Multilevel Brain
                      Organization and Variability (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5253 / G:(DE-HGF)POF4-5251},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/903648},
}