Books / 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

  • Aertsen A., Grün S., Maldonado PE., Palm G. (eds) (2022) Introducing Computation to Neuroscience: Selected papers of George Gerstein. Springer Series in Computational Neuroscience ISBN 978-3-030-87446-9
    DOI: 10.1007/978-3-030-87447-6

  • Lawrie S., Moreno-Bote R., Gilson M. (2022) Covariance Features Improve Low-Resource Reservoir Computing Performance in Multivariate Time Series Classification. In: Smys S., Tavares JMRS., Balas VE. (eds) Computational Vision and Bio-Inspired Computing. Advances in Intelligent Systems and Computing 1420, 587 - 601
    DOI: 10.1007/978-981-16-9573-5_42

2021

  • van Albada S., 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 Th., Petkov N. (eds.) Brain-Inspired Computing Cham: Springer, Lecture Notes in Computer Science 12339:47-59.
    DOI: 10.1007/978-3-030-82427-3


2020

  • Helias M., Dahmen D. (2020) Statistical Field Theory for Neural Networks. Springer International Publishing
    DOI: 10.1007/978-3-030-46444-8


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"


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

  • Denker M., Grün S. (2016) Designing workflows for the reproducible Analysis of Electrophysiological Data in: Amunts K, Grandinetti L, Lippert T, Petkov N: Brain Inspired Computing, Springer Series Lecture Notes in Computer Science, Vol 10087:58-72.
    DOI:10.1007/978-3-319-50862-7_5


  • 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


2015

  • Grün S. (2015) Spike Train Analysis: Overview. In: Jaeger D, Jung R. Book Section, Encyclopedia of Computational Neuroscience, Springer New York,
    DOI:10.1007/978-1-4614-6675-8_776

  • Grün S. (2015) Surrogate Data for Evaluation of Spike Correlation.In: Jaeger D, Jung R: Book Section, Encyclopedia of Computational Neuroscience, Springer New York,
    DOI:10.1007/978-1-4614-6675-8_411


  • Grün S. (2015) Unitary Event AnalysisIn: Jaeger D, Jung R. Book Section, Encyclopedia of Computational Neuroscience, Springer New York,
    DOI:10.1007/978-1-4614-6675-8_412

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


2008


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. In: P. Beim Graben, C. Zhou, M. Thiel, and J. Kurths eds. Lectures in supercomputational neuroscience: dynamics in complex brain networks Chapter IV.10 p 267-278. Springer preprint. 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:
    Lecture Notes in Computer Science, 4729, 428 - 437

  • 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.


2001


1996

  • Grün S. (1996) Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance, and Interpretation. Reihe Physik, Band 60. Verlag Harri Deutsch, Thun, Frankfurt/Main.


1995

  • Aertsen A, Diesmann M, Grün S, Arndt M, Gewaltig MO (1995) Coupling dynamics and coincident spiking in cortical neural networks. In: H. J. Hermann, D. E. Wolf, and E. Pöppel eds. Supercomputing in Brain Research: from Tomography to Neural Networks, 213-223 world Scientific

  • 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

  • Riehle A, Seal J, Requin J, Grün S, Aertsen A (1995) Multi-electrode recording of neuronal activity in the motor cortex: Evidence for changes in the functional coupling between neurons. In: H. J. Hermann, D. E. Wolf, and E. Pöppel eds. upercomputing in Brain Research: from Tomography to Neural Networks, p 281–288. World Scientific.


1994

  • Martignon L, von Hasseln H, Grün S, and Palm G (1994) Modelling the interaction in a set of neurons implicit in their frequency distribution: a possible approach to neural assemblies. In: Collected Lectures of the Seminar on Cybernetics. Rosenberg-Sellier

Last Modified: 19.09.2024