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@INPROCEEDINGS{Pronold:1017849,
      author       = {Pronold, Jari and Meegen, Alexander van and Vollenbröker,
                      Hannah and Shimoura, Renan and Senden, Mario and Hilgetag,
                      Claus C. and Bakker, Rembrandt and van Albada, Sacha},
      title        = {{M}ulti-{S}cale {S}piking {N}etwork {M}odel of {H}uman
                      {C}erebral {C}ortex},
      reportid     = {FZJ-2023-04363},
      year         = {2023},
      note         = {References: [1] Schmidt M, Bakker R, Hilgetag CC, Diesmann
                      M, van Albada SJ. Brain Struct Funct.
                      2018;223(3):1409–35.[2] Schmidt M, Bakker R, Shen K,
                      Bezgin G, Diesmann M, et al. PLOS Comput Biol.
                      2018;14(10):e1006359.[3] Potjans TC, Diesmann M. Cerebral
                      Cortex. 2014;24(3):785–806.[4] Van Essen DC, Smith SM,
                      Barch DM, Behrens TE, Yacoub E, et al. Neuroimage.
                      2013;80:62–79[5] Mohan H, Verhoog MB, Doreswamy KK, Eyal
                      G, Aardse R, et al. Cerebral Cortex.
                      2015;25(12):4839–53.[6] Minxha J, Adolphs R, Fusi S,
                      Mamelak AN, Rutishauser U. Science. 2020;368(6498).},
      abstract     = {Background: The structure of the brain plays a crucial role
                      in shaping its activity. However, the link between
                      structural connectivity and observed neuronal activity
                      remains incompletely understood. Previous research utilizing
                      a large-scale spiking network model of leaky
                      integrate-and-fire neurons has addressed this question for
                      macaque cortex [1,2]. Here, a similar framework is employed
                      to investigate human cortex in a model that links the
                      cortical network structure to the resting-state activity of
                      neurons, populations, layers, and areas.Objectives: The
                      objective of this study is to investigate the link between
                      structural connectivity and observed neuronal activity in
                      human cortex using a large-scale spiking network model, and
                      to create a platform for multi-scale in silico studies of
                      human cortex.Materials and Methods: The model includes all
                      34 areas in a single hemisphere of human cortex according to
                      the Desikan-Killiany parcellation. Our approach integrates
                      cortical data on architecture, morphology, and connectivity
                      into a multi-scale framework for predicting neuron
                      connections. Each cortical area is represented by a 1 $mm^2$
                      layered microcircuit adapted from [3] with the full density
                      of neurons and synapses. Inter-area connectivity relies on
                      diffusion tensor imaging data [4] and the determination of
                      laminar patterns of synaptic connectivity takes into account
                      human neuron morphology data [5]. The model comprises 4
                      million neurons and 50 billion synapses, simulated with the
                      NEST simulator on the supercomputer JURECA-DC. Results and
                      Conclusions: Simulations of the model with uniform synaptic
                      weights reveal a state with asynchronous and irregular
                      activity that deviates from experimental recordings in terms
                      of spiking activity and inter-area functional connectivity.
                      Increasing inter-area synapse strength enables the model to
                      capture both microscopic and macroscopic resting-state
                      activity of human cortex measured via electrophysiological
                      recordings and fMRI [6]. Furthermore, the model reveals
                      rapid propagation of the effects of a single-spike
                      perturbation across the entire network. This suggests
                      individual spikes play a role in fast sensory processing and
                      behavioral responses in the cortical network. Overall, the
                      model serves as a basis for the investigation of multi-scale
                      structure-dynamics relationships in human cortex.},
      month         = {Oct},
      date          = {2023-10-26},
      organization  = {2nd Cologne Neuroscience Day, Cologne
                       (Germany), 26 Oct 2023 - 26 Oct 2023},
      subtyp        = {Other},
      cin          = {INM-6 / IAS-6 / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {5231 - Neuroscientific Foundations (POF4-523) / DFG project
                      313856816 - SPP 2041: Computational Connectomics (313856816)
                      / DFG project 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 $(jinb33_20220812)$},
      pid          = {G:(DE-HGF)POF4-5231 / G:(GEPRIS)313856816 /
                      G:(GEPRIS)347572269 / G:(EU-Grant)945539 /
                      $G:(DE-Juel1)jinb33_20220812$},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/1017849},
}