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@ARTICLE{Lu:1049762,
      author       = {Lu, Han and Diaz, Sandra and Lenz, Maximilian and Vlachos,
                      Andreas},
      title        = {{T}he interplay between homeostatic synaptic scaling and
                      homeostatic structural plasticity maintains the robust
                      firing rate of neural networks},
      journal      = {eLife},
      volume       = {RP88376},
      issn         = {2050-084X},
      address      = {Cambridge},
      publisher    = {eLife Sciences Publications},
      reportid     = {FZJ-2025-05546},
      pages        = {1-32},
      year         = {2025},
      abstract     = {Critical network states and neural plasticity enable
                      adaptive behavior in dynamic environments, supporting
                      efficient information processing and experience-dependent
                      learning. Synaptic-weight-based Hebbian plasticity and
                      homeostatic synaptic scaling are key mechanisms that enable
                      memory while stabilizing network dynamics. However, the role
                      of structural plasticity as a homeostatic mechanism remains
                      less consistently reported, particularly under activity
                      inhibition, leading to an incomplete understanding of its
                      functional impact. In this study, we combined live-cell
                      microscopy of eGFP-labeled neurons in mouse organotypic
                      entorhinal-hippocampal tissue cultures (Thy1-eGFP mice of
                      both sexes) with computational modeling to investigate how
                      synapse-number-based structural plasticity responds to
                      activity perturbations and interacts with homeostatic
                      synaptic scaling. Tracking individual dendritic segments, we
                      found that inhibiting excitatory neurotransmission does not
                      monotonically regulate dendritic spine density.
                      Specifically, inhibition of AMPA receptors with 200 nM
                      2,3-dioxo-6-nitro-7-sulfamoyl-benzo[f]quinoxaline (NBQX)
                      increased spine density, whereas complete AMPA receptor
                      blockade with 50 μM NBQX reduced it. Motivated by these
                      findings, we developed network simulations incorporating a
                      biphasic structural plasticity rule governing
                      activity-dependent synapse formation. These simulations
                      showed that the biphasic rule maintains neural activity
                      homeostasis under stimulation and permits either synapse
                      formation or synapse loss depending on the degree of
                      activity deprivation. Homeostatic synaptic scaling further
                      modulated recurrent connectivity, network activity, and
                      structural plasticity outcomes. It reduced
                      stimulation-triggered synapse loss by downscaling synaptic
                      weights and rescued silencing-induced synapse loss by
                      upscaling recurrent input, thus reactivating silent neurons.
                      The interaction between these mechanisms provides a
                      mechanistic explanation for divergent findings in the
                      literature. In summary, homeostatic synaptic scaling and
                      homeostatic structural plasticity dynamically compete and
                      compensate for each other, ensuring efficient and robust
                      control of firing rate homeostasis.},
      cin          = {JSC},
      ddc          = {600},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / SLNS - SimLab
                      Neuroscience (Helmholtz-SLNS) / JL SMHB - Joint Lab
                      Supercomputing and Modeling for the Human Brain (JL
                      SMHB-2021-2027) / HBP SGA3 - Human Brain Project Specific
                      Grant Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-Juel1)Helmholtz-SLNS /
                      G:(DE-Juel1)JL SMHB-2021-2027 / G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)16},
      doi          = {https://doi.org/10.7554/eLife.88376.3},
      url          = {https://juser.fz-juelich.de/record/1049762},
}