001031473 001__ 1031473 001031473 005__ 20250203133209.0 001031473 0247_ $$2doi$$a10.1093/cercor/bhae409 001031473 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-05686 001031473 0247_ $$2pmid$$a39428578 001031473 0247_ $$2WOS$$aWOS:001336208500001 001031473 037__ $$aFZJ-2024-05686 001031473 041__ $$aEnglish 001031473 082__ $$a610 001031473 1001_ $$0P:(DE-Juel1)165321$$aPronold, Jari$$b0 001031473 245__ $$aMulti-Scale Spiking Network Model of Human Cerebral Cortex 001031473 260__ $$aOxford$$bOxford Univ. Press$$c2024 001031473 3367_ $$2DRIVER$$aarticle 001031473 3367_ $$2DataCite$$aOutput Types/Journal article 001031473 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1730817016_26266 001031473 3367_ $$2BibTeX$$aARTICLE 001031473 3367_ $$2ORCID$$aJOURNAL_ARTICLE 001031473 3367_ $$00$$2EndNote$$aJournal Article 001031473 520__ $$aAlthough the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand the activity. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan–Killiany parcellation is represented by a 1 $mm^2$ column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and diffusion tensor imaging, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity with human electrophysiological data and human resting-state functional magnetic resonance imaging (fMRI) data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the inter-areal connections are sufficiently strong. Furthermore, we study the propagation of a single-spike perturbation and macroscopic fluctuations through the network. The open-source model serves as an integrative platform for further refinements and future in silico studies of human cortical structure, dynamics, and function. 001031473 536__ $$0G:(DE-HGF)POF4-5231$$a5231 - Neuroscientific Foundations (POF4-523)$$cPOF4-523$$fPOF IV$$x0 001031473 536__ $$0G:(GEPRIS)347572269$$aDFG project G:(GEPRIS)347572269 - Heterogenität von Zytoarchitektur, Chemoarchitektur und Konnektivität in einem großskaligen Computermodell der menschlichen Großhirnrinde (347572269)$$c347572269$$x1 001031473 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2 001031473 536__ $$0G:(EU-Grant)101147319$$aEBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health (101147319)$$c101147319$$fHORIZON-INFRA-2022-SERV-B-01$$x3 001031473 536__ $$0G:(DE-Juel1)JL SMHB-2021-2027$$aJL SMHB - Joint Lab Supercomputing and Modeling for the Human Brain (JL SMHB-2021-2027)$$cJL SMHB-2021-2027$$x4 001031473 536__ $$0G:(DE-Juel-1)HiRSE_PS-20220812$$aHelmholtz Platform for Research Software Engineering - 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