% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Kharabian:877237,
      author       = {Kharabian, Shahrzad and Plachti, Anna and Hoffstaedter,
                      Felix and Eickhoff, Simon and GENON, Sarah},
      title        = {{C}haracterizing the gradients of structural covariance in
                      the human hippocampus},
      journal      = {NeuroImage},
      volume       = {218},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {FZJ-2020-02064},
      pages        = {116972},
      year         = {2020},
      abstract     = {The hippocampus is a plastic brain structure that has been
                      associated with a range ofbehavioral aspects but also shows
                      vulnerability to the most frequent neurocognitivediseases.
                      Different aspects of its organization have been revealed by
                      studies probingits different neurobiological properties. In
                      particular, histological work has shown apattern of
                      differentiation along the proximal-distal dimension, while
                      studies examiningfunctional properties and large-scale
                      functional integration have primarily highlighted apattern
                      of differentiation along the anterior-posterior dimension.
                      To better understandhow these organizational dimensions
                      underlie the pattern of structural covariance (SC)in the
                      human hippocampus, we here applied a non-linear
                      decomposition approach,disentangling the major modes of
                      variation, to the pattern of grey matter volumecorrelation
                      of hippocampus voxels with the rest of the brain in a sample
                      of 377 healthyyoung adults. We additionally investigated the
                      consistency of the derived gradients inan independent sample
                      of life-span adults and also examined the
                      relationshipsbetween these major modes of variations and the
                      patterns derived from microstructureand functional
                      connectivity mapping. Our results showed that similar major
                      modes ofSC-variability are identified across the two
                      independent datasets. The major dimensionof variation found
                      in SC runs along the hippocampal anterior-posterior axis
                      andfollowed closely the principal dimension of functional
                      differentiation, suggesting aninfluence of network level
                      interaction in this major mode of morphological
                      variability.The second main mode of variability in the SC
                      showed a gradient along the dorsalventralaxis, and was
                      moderately related to variability in hippocampal
                      microstructuralproperties. Thus our results depicting
                      relatively reliable patterns of SC-variability withinthe
                      hippocampus show an interplay between the already known
                      organizationalprinciples on the pattern of variability in
                      hippocampus' macrostructural properties. Thisstudy hence
                      provides a first insight on the underlying organizational
                      forces generatingdifferent co-plastic modes within the human
                      hippocampus that may, in turn, help tobetter understand
                      different vulnerability patterns of this crucial structure
                      in differentneurological and psychiatric diseases.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {574 - Theory, modelling and simulation (POF3-574)},
      pid          = {G:(DE-HGF)POF3-574},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32454206},
      UT           = {WOS:000555460300011},
      doi          = {10.1016/j.neuroimage.2020.116972},
      url          = {https://juser.fz-juelich.de/record/877237},
}