% 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”.

@PHDTHESIS{Layer:911032,
      author       = {Layer, Moritz},
      title        = {{D}ynamical and statistical structure of spatially
                      organized neuronal networks},
      volume       = {85},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2022-04358},
      isbn         = {978-3-95806-651-9},
      series       = {Schriften des Forschungszentrums Jülich Reihe Information
                      / Information},
      pages        = {xiii, 165},
      year         = {2022},
      note         = {Dissertation, RWTH Aachen University, 2022},
      abstract     = {The cerebral cortex, the outer layer of mammalian brains,
                      comprises a vast number of neurons arranged and connected in
                      a highly organized fashion. The likelihood of neurons to be
                      connected and how fast they may exchange signals depends,
                      among other properties, on their spatial distance. Cortical
                      networks may be well described as completely random networks
                      on microscopic scales because cortical neurons have
                      essentially uniform connection probabilities within a few
                      tens of micrometers. However, the distance-dependence of
                      neuronal connections certainly is important on mesoscopic
                      scales spanning several millimeters, where many neurons are
                      most likely unconnected. While the theory of random networks
                      is already well-established, how such a spatial organization
                      affects a network’s activity is not yet fully understood.
                      The objectiveof this thesis is to provide an overview of the
                      current analytical understanding of spatially organized
                      networks on a mesoscopic scale, as well as to advance this
                      understanding with three studies covering complementary
                      aspects of spatially organized network theory.},
      cin          = {INM-6 / IAS-6},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:0001-2022112310},
      url          = {https://juser.fz-juelich.de/record/911032},
}