Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers

  • Anders LansnerEmail author
  • Markus Diesmann


The number of neurons and synapses in biological brains is very large, on the order of millions and billions respectively even in small animals like insects and mice. By comparison most neuronal network models developed and simulated up to now have been tiny, comprising many orders of magnitude less neurons than their real counterpart, with an even more dramatic difference when it comes to the number of synapses. In this chapter we discuss why and when it may be important to work with large-scale, if not full-scale, neuronal network and brain models and to run simulations on supercomputers. We describe the state-of-the-art in large-scale neural simulation technology and methodology as well as ways to analyze and visualize output from such simulations. Finally we discuss the challenges and future trends in this field.


Graphical Processing Unit Pyramidal Cell Neuronal Network Neuron Model Local Field Potential 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Partially funded by EU Grant 15879 (FACETS), BMBF Grant 01GQ0420 to the Bernstein Center Freiburg, Next-Generation Supercomputer Project of MEXT, the Helmholtz Alliance on Systems Biology, the Swedish Science Council (VR-621-2004-3807), VINNOVA (Swedish Governmental Agency for Innovation Systems), the Swedish Foundation for Strategic Research (through the Stockholm Brain Institute), and the European Union grants 15879 (FACETS) and 269921 (BrainScaleS). Access to supercomputing facility through JUGENE-Grant JINB33. We also thank the DEISA Consortium (, co-funded through the EU FP6 project RI-031513 and the FP7 project RI-222919, for support within the DEISA Extreme Computing Initiative.


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© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of Numerical Analysis and Computer ScienceStockholm UniversityStockholmSweden
  2. 2.Department of Computational Biology, School of Computer Science and CommunicationRoyal Institute of TechnologyStockholmSweden
  3. 3.Institute of Neuroscience and Medicine (INM-6), Computational and Systems NeuroscienceResearch Center JuelichJuelichGermany
  4. 4.Faculty of MedicineRWTH Aachen UniversityAachenGermany
  5. 5.RIKEN Brain Science InstituteWako CityJapan

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