Book chapters

2024

  • Korcsak-Gorzo A., Linssen C., Albers J., Dasbach S., Duarte R., Kunkel S., Morrison A., Senk J., Stapmanns J., Tetzlaff T., Diesmann M., van Albada SJ. (2024) Phenomenological Modeling of Diverse and Heterogeneous Synaptic Dynamics at Natural Density. In: Lübke, J.H., Rollenhagen, A. (eds) New Aspects in Analyzing the Synaptic Organization of the Brain. Neuromethods, vol 212. DOI: 10.1007/978-1-0716-4019-7_15

2022

  • van Albada, SJ., Morales-Gregorio, A., Dickscheid T., Goulas A., Bakker R. Bludau S., Palm G., Hilgetag CC., Diesmann M. (2022). Bringing Anatomical Information into Neuronal Network Models. In: Giugliano, M., Negrello, M., Linaro, D. (eds) Computational Modelling of the Brain. Advances in Experimental Medicine and Biology, 1359.
    DOI: 10.1007/978-3-030-89439-9_9


2021

  • 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. Springer, Lecture Notes in Computer Science 12339:47-59.
    DOI: 10.1007/978-3-030-82427-3_4


2018

  • 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" https://juser.fz-juelich.de/record/844769

2017

  • 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

2016

  • Hahne J., Helias M., Kunkel S., Igarashi J., Kitayama J., 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 Brain Comp 2015. Lecture Notes in Computer Science, Vol 10087, pp 43-57. DOI: 10.1007/978-3-319-50862-7_4

2014

  • 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

2013

  • Potjans T., Diesmann M. (2013) Multi-population Network Models of the Cortical Microcircuit. In: Y. Yamaguchi ed. Advances in Cognitive Neuroscience (III) p 91-96. Springer. DOI:10.1007/987-94-007-4792-0_13

  • Trengove C., van Leeuwen C., Diesmann M. (2013) Complex Network Topology and Dynamics in Networks Supporting Precisely-Timed Activity Patterns. In: Y. Yamaguchi ed. Advances in Cognitive Neuroscience (III) p 317-322. Springer. DOI: 10.1007/978-94-007-4792-0_43

2012

  • 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. NIC Symposium 2012, Editors: Klaus Binder, Gernot Münster, Manfred Kremer. Proceedings, Forschungszentrum Jülich NIC Series Vol. 45, page 81 ISBN 978-3-89336-758-0. http://juser.fz-juelich.de/record/21739

  • Lansner A., Diesmann M. (2012) Virtues, pitfalls, and methodology of neuronal network modeling and simulations on supercomputers. in Nicolas Le Novére Computational Systems Biology, Chapt. 10, Springer, ISBN 978-94-007-3857-7. DOI: 10.1007/978-94-007-3858-4_10

2010

  • Grün S., Diesmann M., Aertsen A. (2010) Unitary event analysis. In: Sonja Grün, Stefan Rotter eds. Analysis of Parallel Spike Trains Chapter 10, 191-220 Springer. DOI: 10.1007/978-1-4419-5675-0_10

  • Tetzlaff T., Diesmann M. (2010) Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale. In: Sonja Grün, Stefan Rotter eds. Analysis of Parallel Spike Trains Chapter 6 103-127. Springer. DOI: 10.1007/978-1-4419-5675-0_6

  • Denker M., Wiebelt B., Fliegner D., Diesmann M., Morrison A. (2010) Practically trivial parallel data processing in a neuroscience laboratory. In: Sonja Grün, Stefan Rotter eds. Analysis of Parallel Spike Trains Chapter 20 413-436. Springer. DOI: 10.1007/978-1-4419-5675-0_20

2008

  • 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

2007

  • Eppler JM., Plesser HE., Morrison A., Diesmann M., Gewaltig MO. (2007) Multithreaded and distributed simulation of large biological neuronal networks. In: Cappello, F, Herault, T, Dongarra J eds. Recent Advances in Parallel Virtual Machine and Message Passing Interface 4757. Springer. DOI: 10.1007/978-3-540-75416-9_55

  • Morrison A., Diesmann M. (2007) Maintaining Causality in Discrete Time Neuronal Network Simulations. Chap 10, pp 267–278 In: Graben P.b., Zhou C., Thiel M., Kurths J. (eds) Lectures in Supercomputational Neurosciences. Understanding Complex Systems. Springer, Berlin, Heidelberg.
    DOI: 10.1007/978-3-540-73159-7_10

  • 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


2002

  • Diesmann M., Gewaltig MO. (2002) NEST: An environment for neural systems. In: Plessert T., Macho V. (eds). Forschung und wissenschaftliches Rechnen, Beiträge zum Heinz-Billing-Preis 2001 Ges. für Wiss. Datenverarbeitung 58: 43-70.
    To download the article, click here.

1995

  • Gewaltig MO., Diesmann M., Aertsen A. (1995) Propagation of Synfire Activity in Cortical Networks: a Statistical Approach. In: Kappen, B, Gielen, S eds. Neural Networks: Artificial Intelligence and Industrial Applications 37-40. Springer. DOI: 10.1007/978-1-4471-3087-1_6

Last Modified: 19.09.2024