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@INPROCEEDINGS{Shimoura:1047386,
      author       = {Shimoura, Renan},
      title        = {{M}ulti-{A}rea {C}ortical {M}odels: {B}ridging {S}tructure
                      and {D}ynamics in {L}arge-{S}cale {S}piking {N}etworks},
      reportid     = {FZJ-2025-04272},
      year         = {2025},
      note         = {References: [1] Schmidt, M., Bakker, R., Hilgetag, C. C.,
                      Diesmann, M., $\&$ van Albada, S. J. (2018). Multi-scale
                      account of the network structure of macaque visual cortex.
                      Brain Structure $\&$ Function, 223(3), 1409–1435. [2]
                      Schmidt, M., Bakker, R., Shen, K., Bezgin, G., Diesmann, M.,
                      $\&$ van Albada, S. J. (2018). A multi-scale layer-resolved
                      spiking network model of resting-state dynamics in macaque
                      visual cortical areas. PLoS Computational Biology, 14(10),
                      e1006359. [3] Pronold, J., van Meegen, A., Shimoura, R. O.,
                      Vollenbröker, H., Senden, M., Hilgetag, C. C., Bakker, R.,
                      $\&$ van Albada, S. J. (2024). Multi-scale spiking network
                      model of human cerebral cortex. Cerebral Cortex, 34(10),
                      bhae409. [4] Pronold, J., Morales-Gregorio, A., Rostami, V.,
                      $\&$ van Albada, S. J. (2024). Cortical multi-area model
                      with joint excitatory-inhibitory clusters accounts for
                      spiking statistics, inter-area propagation, and variability
                      dynamics. bioRxiv.},
      abstract     = {In recent years, we have developed multiscale spiking
                      networks that bridge local circuits and cortical areas, as
                      illustrated by the macaque visual cortex [1, 2] and the
                      human cerebral cortex models [3]. These models serve as
                      platforms for linking anatomical structure to emergent
                      network dynamics. For instance, in Pronold et al. [4], we
                      extended the macaque multi-area model by implementing joint
                      excitatory-inhibitory (EI) clustering. This clustered
                      architecture adjusts resting-state spiking activity
                      statistics, supports robust signal propagation across the
                      hierarchy, and reproduces the experimentally observed
                      reduction of neural variability upon stimulation. However,
                      scaling into this structure poses a significant
                      computational bottleneck, causing network construction time
                      in the NEST simulator to increase substantially (e.g., from
                      one minute to several hours for 50 clusters). To address
                      this initialization challenge, strategies include code
                      refactoring and developing specialized connection routines
                      within the core NEST framework. The NEST-GPU platform
                      presents a potential alternative for assessing new network
                      initialization strategies. Additionally, it may offer an
                      effective environment for accelerating the simulation
                      dynamics of these massive networks at full scale.},
      month         = {Oct},
      date          = {2025-10-08},
      organization  = {NEST GPU Workshop, Cagliari (Italy), 8
                       Oct 2025 - 15 Oct 2025},
      subtyp        = {Invited},
      cin          = {IAS-6},
      cid          = {I:(DE-Juel1)IAS-6-20130828},
      pnm          = {5231 - Neuroscientific Foundations (POF4-523) / DFG project
                      G:(GEPRIS)347572269 - Heterogenität von Zytoarchitektur,
                      Chemoarchitektur und Konnektivität in einem großskaligen
                      Computermodell der menschlichen Großhirnrinde (347572269) /
                      HBP SGA3 - Human Brain Project Specific Grant Agreement 3
                      (945539) / Brain-Scale Simulations $(jinb33_20220812)$ /
                      EBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to
                      Advance Neuroscience and Brain Health (101147319) / JL SMHB
                      - Joint Lab Supercomputing and Modeling for the Human Brain
                      (JL SMHB-2021-2027)},
      pid          = {G:(DE-HGF)POF4-5231 / G:(GEPRIS)347572269 /
                      G:(EU-Grant)945539 / $G:(DE-Juel1)jinb33_20220812$ /
                      G:(EU-Grant)101147319 / G:(DE-Juel1)JL SMHB-2021-2027},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/1047386},
}