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Book-Chapters of Computational Neurophysics

  • 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"
  • Senk J., Yegenoglu A., Amblet O., Brukau Y., Davison A., Lester DR., Lührs A., Quaglio P., Rostami V., Rowley A., Schuller B., Stokes AB., van Albada SJ., Zielasko D., Diesmann M., Weyers B., Denker M., Grün S. (2017). A collaborative simulation-analysis workflow for computational neuroscience using hpc. In: Di Napoli E, Hermanns M-A, Iliev H, Lintermann A, Peyser A eds. High-Performance Scientific Computing. Cham: Springer International Publishing, 243–256. DOI: 10.1007/978-3-319-53862-4_21.
  • Hahne J., Helias M., Kunkel S., Igarashi J., Kitayama I., Wylie B., Bolten M., Frommer A., Diesmann M. (2016). Including gap junctions into distributed neuronal network simulations. In: Amunts K, Grandinetti L, Lippert T, Petkov N eds. Brain-Inspired Computing. Cham: Springer International Publishing, 43–57. DOI: 10.1007/978-3-319-50862-7_4.
  • 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.
  • Kunkel S., Helias M., Potjans TC., Eppler JM., Plesser HE., Diesmann M., Morrison A. (2012). Memory consumption of neuronal network simulators at the brain scale. In: Binder K, Münster M, Kremer M eds. NIC Symposium 2012. NIC Series. Jülich: Forschungszentrum Jülich, 81–88.
  • Lansner, A., Diesmann, M. (2012) Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers Computational Systems Biology Dordrecht : Springer Netherlands 283-315 10.1007/978-94-007-3858-4_10
  • Grün S., Abeles M., Diesmann M. (2008). Impact of higher-order correlations on coincidence distributions of massively parallel data. In: Marinaro M, Scarpetta S, Yamaguchi Y eds. Dynamic Brain - from Neural Spikes to Behaviors. Berlin, Heidelberg: Springer Berlin Heidelberg, 96–114. DOI: 10.1007/978-3-540-88853-6_8.
  • Pazienti A., Diesmann M., Grün S. (2007). Bounds of the ability to destroy precise coincidences by spike dithering. In: Mele F, Ramella G, Santillo S, Ventriglia F eds. Advances in Brain, Vision, and Artificial Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 428–437. DOI: 10.1007/978-3-540-75555-5_41.
  • Plesser HE., Eppler JM., Morrison A., Diesmann M., Gewaltig M-O. (2007). Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers. In: Kermarrec A-M, Bougé L, Priol T eds. Euro-Par 2007 Parallel Processing. Berlin, Heidelberg: Springer Berlin Heidelberg, 672–681. DOI: 10.1007/978-3-540-74466-5_71.