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@ARTICLE{Butz:153449,
      author       = {Butz, Markus and Steenbuck, Ines D. and van Ooyen, Arjen},
      title        = {{H}omeostatic structural plasticity increases the
                      efficiency of small-world networks},
      journal      = {Frontiers in synaptic neuroscience},
      volume       = {6},
      number       = {7},
      issn         = {1663-3563},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2014-03056},
      pages        = {14},
      year         = {2014},
      abstract     = {In networks with small-world topology, which are
                      characterized by a high clustering coefficient and a short
                      characteristic path length, information can be transmitted
                      efficiently and at relatively low costs. The brain is
                      composed of small-world networks, and evolution may have
                      optimized brain connectivity for efficient information
                      processing. Despite many studies on the impact of topology
                      on information processing in neuronal networks, little is
                      known about the development of network topology and the
                      emergence of efficient small-world networks. We investigated
                      how a simple growth process that favors short-range
                      connections over long-range connections in combination with
                      a synapse formation rule that generates homeostasis in
                      post-synaptic firing rates shapes neuronal network topology.
                      Interestingly, we found that small-world networks benefited
                      from homeostasis by an increase in efficiency, defined as
                      the averaged inverse of the shortest paths through the
                      network. Efficiency particularly increased as small-world
                      networks approached the desired level of electrical
                      activity. Ultimately, homeostatic small-world networks
                      became almost as efficient as random networks. The increase
                      in efficiency was caused by the emergent property of the
                      homeostatic growth process that neurons started forming more
                      long-range connections, albeit at a low rate, when their
                      electrical activity was close to the homeostatic set-point.
                      Although global network topology continued to change when
                      neuronal activities were around the homeostatic equilibrium,
                      the small-world property of the network was maintained over
                      the entire course of development. Our results may help
                      understand how complex systems such as the brain could set
                      up an efficient network topology in a self-organizing
                      manner. Insights from our work may also lead to novel
                      techniques for constructing large-scale neuronal networks by
                      self-organization.},
      cin          = {JSC / JARA-HPC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$},
      pnm          = {411 - Computational Science and Mathematical Methods
                      (POF2-411) / SMHB - Supercomputing and Modelling for the
                      Human Brain (HGF-SMHB-2013-2017) / SLNS - SimLab
                      Neuroscience (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF2-411 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
                      G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:24744727},
      doi          = {10.3389/fnsyn.2014.00007},
      url          = {https://juser.fz-juelich.de/record/153449},
}