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@ARTICLE{Schnellbcher:873911,
      author       = {Schnellbächer, Gereon J. and Hoffstaedter, Felix and
                      Eickhoff, Simon B. and Caspers, Svenja and Nickl-Jockschat,
                      Thomas and Fox, Peter T. and Laird, Angela R. and Schulz,
                      Jörg B. and Reetz, Kathrin and Dogan, Imis},
      title        = {{F}unctional {C}haracterization of {A}trophy {P}atterns
                      {R}elated to {C}ognitive {I}mpairment},
      journal      = {Frontiers in neurology},
      volume       = {11},
      issn         = {1664-2295},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2020-01096},
      pages        = {18},
      year         = {2020},
      note         = {FUNDINGKR was funded by the German Federal Ministry of
                      Educationand Research (BMBF 01GQ1402). ID was supported by
                      theSTART-Program(08/16) of the Faculty of Medicine at
                      theRWTHAachen University.},
      abstract     = {Introduction: Mild cognitive impairment (MCI) is a
                      heterogenous syndrome considered as a risk factor for
                      developing dementia. Previous work examining morphological
                      brain changes in MCI has identified a temporo-parietal
                      atrophy pattern that suggests a common neuroanatomical
                      denominator of cognitive impairment. Using functional
                      connectivity analyses of structurally affected regions in
                      MCI, we aimed to investigate and characterize functional
                      networks formed by these regions that appear to be
                      particularly vulnerable to disease-related disruptions.
                      Methods: Areas of convergent atrophy in MCI were derived
                      from a quantitative meta-analysis and encompassed left and
                      right medial temporal (i.e., hippocampus, amygdala), as well
                      as parietal regions (precuneus), which were defined as seed
                      regions for connectivity analyses. Both task-based
                      meta-analytical connectivity modeling (MACM) based on the
                      BrainMap database and task-free resting-state functional MRI
                      in a large cohort of older adults from the 1000BRAINS study
                      were applied. We additionally assessed behavioral
                      characteristics associated with the seed regions using
                      BrainMap meta-data and investigated correlations of
                      resting-state connectivity with age. Results: The left
                      temporal seed showed stronger associations with a
                      fronto-temporal network, whereas the right temporal atrophy
                      cluster was more linked to cortico-striatal regions. In
                      accordance with this, behavioral analysis indicated an
                      emphasis of the left temporal seed on language generation,
                      and the right temporal seed was associated with the domains
                      of emotion and attention. Task-independent co-activation was
                      more pronounced in the parietal seed, which demonstrated
                      stronger connectivity with a frontoparietal network and
                      associations with introspection and social cognition.
                      Correlation analysis revealed both decreasing and increasing
                      functional connectivity with higher age that may add to
                      pathological processes but also indicates compensatory
                      mechanisms of functional reorganization with increasing age.
                      Conclusion: Our findings provide an important
                      pathophysiological link between morphological changes and
                      the clinical relevance of major structural damage in MCI.
                      Multimodal analysis of functional networks related to areas
                      of MCI-typical atrophy may help to explain cognitive decline
                      and behavioral alterations not tractable by a mere
                      anatomical interpretation and therefore contribute to
                      prognostic evaluations.Copyright © 2020 Schnellbächer,
                      Hoffstaedter, Eickhoff, Caspers, Nickl-Jockschat, Fox,
                      Laird, Schulz, Reetz and Dogan.},
      cin          = {INM-7 / INM-1 / INM-11},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)INM-1-20090406 /
                      I:(DE-Juel1)INM-11-20170113},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572)},
      pid          = {G:(DE-HGF)POF3-572},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32038473},
      UT           = {WOS:000529929300001},
      doi          = {10.3389/fneur.2020.00018},
      url          = {https://juser.fz-juelich.de/record/873911},
}