Spiking Neural Network Simulations

Spiking Neural Network Simulations

Copyright: Overview of a multi-area model of the vision-related areas of macaque cortex (Schmidt et al., 2018 PLoS Comput Biol & Schmidt et al., 2018 Brain Struct Func)

There are many open questions concerning the links between the neuronal connectivity structure, dynamics, and function of the cerebral cortex. Two main complementary modeling approaches exist for addressing these questions: a bottom-up approach in which wide-ranging experimental data are brought together into coherent models; and a top-down approach in which hypotheses about network function and dynamics are implemented and their conformity with biological data tested and improved afterward. In our group, we mainly follow the former approach to develop large-scale spiking network models of primate and human cortices. However, this bottom-up approach is complemented with top-down approaches where useful (see section “Mean-Field Modeling and Theory”).

In Jülich, we are in the unique position of having supercomputational facilities as well as the simulation technology of NEST available for performing massive-scale simulations of mammalian cerebral cortex. In this endeavor, we focus primarily on the resting state as a ground state on which the functional dynamics of cortex unfolds. This is intended as a stepping-stone toward investigations of cortical information processing supported by the anatomical and dynamical substrate.


  • Maksimov A., Diesmann M., van Albada SJ. (2018) Criteria on Balance, Stability and Excitability in Cortical Networks for Constraining Computational Models. Frontiers in Computational Neuroscience 12: 44.
    DOI: 10.3389/fncom.2018.00044

  • Schmidt M., Bakker R., Hilgetag CC., Diesmann M., van Albada SJ. (2018) Multi-scale account of the network structure of macaque visual cortex. Brain Structure and Function 223:1409-1435.
    DOI: 10.1007/s00429-017-1554-4.

  • Hagen E., Dahmen D., Stavrinou ML., Lindén H., Tetzlaff T., van Albada SJ., Grün S., Diesmann M., Einevoll GT. (2016) Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks. Cerebral Cortex 26:4461–4496.
    DOI: 10.1093/cercor/bhw237.

  • Maksimov A, van Albada SJ. , Diesmann M. (2016) [Re] Cellular and Network Mechanisms of Slow Oscillatory Activity (<1 Hz) and Wave Propagations in a Cortical Network Model. Rescience.

  • Kerr CC., van Albada SJ., Neymotin SA., Chadderdon GL., Robinson PA., Lytton WW. (2013) Cortical information flow in Parkinson’s disease: a composite network/field model. Frontiers in Computational Neuroscience 7:39.
    DOI: 10.3389/fncom.2013.00039

Book Chapters

  • van Albada SJ., Pronold J., van Meegen A., Diesmann M. (2021) Usage and Scaling of an Open-Source Spiking Multi-Area Model of Monkey Cortex. In: Amunts K., Grandinetti L., Lippert T., Petkov N. eds. Brain-Inspired Computing. Cham : Springer, Lecture Notes in Computer Science 12339, 47-59.
    DOI: 10.1007/978-3-030-82427-3_4

  • Schmidt M., Diesmann M., van Albada SJ. (2018) Necessity and feasibility of large-scale neuronal network simulations. In: Lecture Notes of the 49th IFF Spring School “Physics of Life"

  • van Albada SJ., Kunkel S., Morrison A., Diesmann M. (2014) Integrating Brain Structure and Dynamics on Supercomputers. In: Grandinetti L., Lippert T., Petkov N. eds. Brain-Inspired Computing LNCS 8603:22-32.
    DOI: 10.1007/978-3-319-12084-3_3


Institute - Internal Contributors

  • Agnes Korcsak-Gorzo

  • Aitor Morales-Gregorio

  • Alexander van Meegen

  • Anno Kurth

  • Han-Jia Jiang

  • Jari Pronold

  • Jasper Albers

  • Dr. Rembrandt Bakker

  • Dr. Renan Shimoura

Collaborations (external)

  • Prof. Timo Dickscheid, INM-1, Forschungszentrum Jülich, Germany

  • Dr. Sebastian Bludau, INM-1, Forschungszentrum Jülich, Germany

  • Prof. Claus Hilgetag, UKE Hamburg, Germany

  • Dr. Thomas Brochier, INT, CNRS, Marseille, France

  • Dr. Bjørg Kilavik, INT, CNRS, Marseille, France

  • Prof. Georgia Gregoriou, University of Crete, Greece

  • Prof. Martin Nawrot, University of Cologne, Germany

  • Dr. Vahid Rostami, University of Cologne, Germany


  • European Union Horizon 2020 research and innovation program (Grant 945539, Human Brain Project, SGA3) (2020‒2023)

  • “Cellular, connectional and molecular heterogeneity in a large-scale computational model of the human cerebral cortex“, Deutsche Forschungsgemeinschaft Grant in the Priority Program “Computational Connectomics” (SPP 2041) (2021‒2024)

  • “Integrating multi-scale connectivity and brain architecture in a large-scale computational model of the human cerebral cortex”, Deutsche Forschungsgemeinschaft Grant in the Priority Program “Computational Connectomics” (SPP 2041) (2018‒2021)

  • European Union Horizon 2020 research and innovation program (Grant 785907, Human Brain Project, SGA2) (2017‒2020)

Last Modified: 16.05.2022