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@ARTICLE{Paquola:909576,
      author       = {Paquola, Casey and Amunts, Katrin and Evans, Alan and
                      Smallwood, Jonathan and Bernhardt, Boris},
      title        = {{C}losing the mechanistic gap: the value of
                      microarchitecture in understanding cognitive networks},
      journal      = {Trends in cognitive sciences},
      volume       = {26},
      number       = {10},
      issn         = {1364-6613},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2022-03258},
      pages        = {873-886},
      year         = {2022},
      abstract     = {Cognitive neuroscience aims to provide biologically
                      relevant accounts of cognition. Contemporary research
                      linking spatial patterns of neural activity to psychological
                      constructs describes 'where' hypothesised functions occur,
                      but not 'how' these regions contribute to cognition.
                      Technological, empirical, and conceptual advances allow this
                      mechanistic gap to be closed by embedding patterns of
                      functional activity in macro- and microscale descriptions of
                      brain organisation. Recent work on the default mode network
                      (DMN) and the multiple demand network (MDN), for example,
                      highlights a microarchitectural landscape that may explain
                      how activity in these networks integrates varied
                      information, thus providing an anatomical foundation that
                      will help to explain how these networks contribute to many
                      different cognitive states. This perspective highlights
                      emerging insights into how microarchitecture can constrain
                      network accounts of human cognition},
      cin          = {INM-1},
      ddc          = {150},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      HIBALL - Helmholtz International BigBrain Analytics and
                      Learning Laboratory (HIBALL) (InterLabs-0015) / HBP SGA3 -
                      Human Brain Project Specific Grant Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)InterLabs-0015 /
                      G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {35909021},
      UT           = {WOS:000864585600009},
      doi          = {10.1016/j.tics.2022.07.001},
      url          = {https://juser.fz-juelich.de/record/909576},
}