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@ARTICLE{Yoo:1024849,
      author       = {Yoo, Seulki and Jang, Yurim and Hong, Seok-Jun and Park,
                      Hyunjin and Valk, Sofie L. and Bernhardt, Boris C. and Park,
                      Bo-yong},
      title        = {{W}hole-brain structural connectome asymmetry in autism},
      journal      = {NeuroImage},
      volume       = {288},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {FZJ-2024-02515},
      pages        = {120534 -},
      year         = {2024},
      abstract     = {Autism spectrum disorder is a common neurodevelopmental
                      condition that manifests as a disruption in sensory and
                      social skills. Although it has been shown that the brain
                      morphology of individuals with autism is asymmetric, how
                      this differentially affects the structural connectome
                      organization of each hemisphere remains under-investigated.
                      We studied whole-brain structural connectivity-based brain
                      asymmetry in individuals with autism using diffusion
                      magnetic resonance imaging obtained from the Autism Brain
                      Imaging Data Exchange initiative. By leveraging
                      dimensionality reduction techniques, we constructed
                      low-dimensional representations of structural connectivity
                      and calculated their asymmetry index. Comparing the
                      asymmetry index between individuals with autism and
                      neurotypical controls, we found atypical structural
                      connectome asymmetry in the sensory and default-mode
                      regions, particularly showing weaker asymmetry towards the
                      right hemisphere in autism. Network communication provided
                      topological underpinnings by demonstrating that the inferior
                      temporal cortex and limbic and frontoparietal regions showed
                      reduced global network communication efficiency and
                      decreased send-receive network navigation in the inferior
                      temporal and lateral visual cortices in individuals with
                      autism. Finally, supervised machine learning revealed that
                      structural connectome asymmetry could be used as a measure
                      for predicting communication-related autistic symptoms and
                      nonverbal intelligence. Our findings provide insights into
                      macroscale structural connectome alterations in autism and
                      their topological underpinnings.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5252 - Brain Dysfunction and Plasticity (POF4-525) / 5251 -
                      Multilevel Brain Organization and Variability (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5252 / G:(DE-HGF)POF4-5251},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {38340881},
      UT           = {WOS:001185401200001},
      doi          = {10.1016/j.neuroimage.2024.120534},
      url          = {https://juser.fz-juelich.de/record/1024849},
}