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@PHDTHESIS{Essink:998199,
      author       = {Essink, Simon},
      othercontributors = {Grün, Sonja Annemarie and Kampa, Björn M.},
      title        = {{N}eural activity dynamics in experimental recordings and
                      simulated networks},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2024-11193},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2023},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2025; Dissertation, RWTH Aachen University, 2023},
      abstract     = {Empirical, data-driven approaches and theoretical,
                      model-driven approaches to investigate the brain largely
                      co-exist. With the intention to foster synergies, this
                      thesis explores the intricacies of each of these two
                      approaches. In the first study, we investigate the neural
                      underpinnings of eye-hand coordination by analyzing spiking
                      activity recorded via multi-electrode arrays from behaving
                      monkeys within the Vision-for-Action experiment. Before
                      exploring movement-related activity along the dorsal visual
                      stream, we follow the dataset's evolution from the raw
                      recording data to preprocessed datasets with integrated
                      metadata as well as spike sorting, and deal with potential
                      artifacts by characterizing and excluding them. To isolate
                      the effect of movement variables from simultaneously
                      occurring behaviors (e.g., vision and eye movements) on the
                      spiking activity of single neurons, we use Generalized
                      Linear Models (GLMs). In particular, we reproduce the
                      observation of a bimodal distribution of preferred
                      directions of neurons in M1/PMd for hand movements
                      restricted to the horizontal plane and report similar
                      bimodal distributions in V1/V2, DP, 7a.In a second project,
                      we research high-frequency oscillations (~300 Hz) that are
                      predicted by simulations of biologically constrained,
                      large-scale, spiking neural network models of a cortical
                      microcircuit. To understand the model prediction
                      mechanistically, we approximate the network dynamics via
                      mean-field and linear response theory and find three network
                      ingredients that impact the power spectrum of the population
                      activity: the anatomical connectivity, the delay
                      distributions, and the transfer functions. Assuming the
                      model prediction is accurate, we argue that high-frequency
                      oscillations should be detectable via population measures as
                      the local field potential.},
      cin          = {163110 / 160000},
      ddc          = {570},
      cid          = {$I:(DE-82)163110_20180110$ / $I:(DE-82)160000_20140620$},
      pnm          = {HBP SGA2 - Human Brain Project Specific Grant Agreement 2
                      (785907) / HBP SGA3 - Human Brain Project Specific Grant
                      Agreement 3 (945539) / GRK 2416 - GRK 2416:
                      MultiSenses-MultiScales: Neue Ansätze zur Aufklärung
                      neuronaler multisensorischer Integration (368482240)},
      pid          = {G:(EU-Grant)785907 / G:(EU-Grant)945539 /
                      G:(GEPRIS)368482240},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2024-11193},
      url          = {https://publications.rwth-aachen.de/record/998199},
}