Hans Ekkehard Plesser: Publications

Peer-reviewed journal papers

  1. E. Nordlie and H. E. Plesser.
    Visualizing neuronal network connectivity with connectivity pattern tables.
    Front. Neuroinform., 3:39, 2010. DOI 10.3389/neuro.11.039.2009.
  2. H. E. Plesser and A. G. Jahnsen.
    Re-seeding invalidates tests of random number generators.
    Appl Math and Comput, , 2010. DOI 10.1016/j.amc.2010.05.066. Preprint.
  3. E. Nordlie, M.-O. Gewaltig, and H. E. Plesser.
    Towards reproducible descriptions of neuronal network models.
    PLoS Comput Biol, 5(8):e1000456, Aug 2009. DOI 10.1371/journal.pcbi.1000456.
  4. H. E. Plesser and M. Diesmann.
    Simplicity and efficiency of integrate-and-fire neuron models..
    Neural Comput, 21:353-359, 2009. DOI 10.1162/neco.2008.03-08-731. Preprint.
  5. A. Morrison, S. Straube, H. E. Plesser, and M. Diesmann.
    Exact subthreshold integration with continuous spike times in discrete time neural network simulations.
    Neural Comput, 19:47-79, 2007. Reprint.
  6. G. T. Einevoll and H. E. Plesser.
    Response of the difference-of-gaussians model to circular drifting-grating patches.
    Visual Neurosci, 22:437-446, 2005.
  7. G. T. Einevoll and H. E. Plesser.
    Linear mechanistic models for the dorsal lateral geniculate nucleus of cat probed using drifting grating stimuli.
    Network-Comp Neural, 13:503-530, 2002. Reprint.
  8. H. E. Plesser and T. Geisel.
    Stochastic resonance in neuron models: Endogenous stimulation revisited.
    Phys Rev E, 63:031916-1-6, 2001. Reprint.
  9. H. E. Plesser and W. Gerstner.
    Noise in integrate-and-fire neurons: from stochastic input to escape rates.
    Neural Comput, 12:367-384, 2000. DOI 10.1162/089976600300015835. Reprint.
  10. H. E. Plesser and T. Geisel.
    Markov analysis of stochastic resonance in a periodically driven integrate-and-fire neuron.
    Phys Rev E, 59:7008-7017, 1999. Reprint.
  11. H. E. Plesser and S. Tanaka.
    Stochastic resonance in a model neuron with reset.
    Phys Lett A, 225:228-234, 1997.

Peer-reviewed conference contributions

  1. H. E. Plesser, J. M. Eppler, A. Morrison, M. Diesmann, and M.-O. Gewaltig.
    Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers.
    In A.-M. Kermarrec, L. Bougé, and T. Priol, editors, Euro-Par 2007: Parallel Processing, volume 4641 of Lecture Notes in Computer Science, pages 672-681, Berlin, 2007. Springer-Verlag. DOI 10.1007/978-3-540-74466-5. Reprint.
  2. H. E. Plesser, G. T. Einevoll, and P. Heggelund.
    Mechanistic modeling of the retinogeniculate circuit in cat.
    Neurocomputing, 44-46:973-978, 2002.
  3. H. E. Plesser and T. Geisel.
    Signal processing by means of noise.
    Neurocomputing, 38-40:307-312, 2001.
  4. H. E. Plesser and W. Gerstner.
    Escape rate models for noisy integrate-and-fire neurons.
    Neurocomputing, 32-33:219-224, 2000.
  5. H. E. Plesser and T. Geisel.
    Bandpass properties of integrate-fire neurons.
    Neurocomputing, 26-27:229-235, 1999.

Book chapters

  1. H. E. Plesser.
    Generating random numbers.
    In S. Grün and S. Rotter, editors, Analysis of Parallel Spike Trains, Springer Series in Computational Neuroscience. Springer Verlag, 2010.
    To appear.

Theses

  1. H. E. Plesser.
    Aspects of Signal Processing in Noisy Neurons.
    PhD thesis, Georg-August-Universität, Göttingen, 1999. Online version. Reprint.
  2. H. E. Plesser.
    Untersuchungen über die Anwendbarkeit stochastischer Verfahren zur Lösung partieller Differentialgleichungen.
    Master's thesis, RWTH Aachen, Aachen, 1995.

Conference Abstracts

  1. S. Kunkel, J. M. Eppler, H. E. Plesser, M.-O. Gewaltig, M. Diesmann, and A. Morrison.
    NEST: Science-driven development of neuronal network simulation software.
    In Frontiers in Neuroscience. Conference Abstract: Neuroinformatics 2010, 2010. DOI 10.3389/conf.fnins.2010.13.00105.
  2. T. C. Potjans, S. Kunkel, A. Morrison, H. E. Plesser, R. Kötter, and M. Diesmann.
    Brain-scale neuronal network simulations: linking local microcircuitry and macroscopic connectivity.
    In 2nd Bio-Supercomputing Symposium Abstracts, Tokyo, Japan, March 2010.
  3. T. C. Potjans, S. Kunkel, A. Morrison, H. E. Plesser, R. Kötter, and M. Diesmann.
    Brain-scale simulations with NEST: supercomputers as data integration facilities.
    In Frontiers in Neuroscience. Conference Abstract: Neuroinformatics 2010, 2010. DOI 10.3389/conf.fnins.2010.13.00096.
  4. J. M. Eppler, R. Kupper, H. E. Plesser, and M. Diesmann.
    A testsuite for a neural simulation engine.
    In Frontiers in Neuroinformatics. Conference Abstract: 2nd INCF Congress of Neuroinformatics, Plzen, 2009. International Neuroinformatics Coordinating Facility. DOI 10.3389/conf.neuro.11.2009.08.042.
  5. H. E. Plesser and K. Austvoll.
    Specification and generation of structured neuronal network models with the NEST Topology module.
    BMC Neuroscience, 10 (Suppl 1):P56, 2009. DOI 10.1186/1471-2202-10-S1-P56.
  6. H. E. Plesser, E. Nordlie, and M.-O. Gewaltig.
    Concise and informative diagrams of neuronal network models: a proposal.
    In Neuroscience Meeting Planner, Chicago, IL, 2009. Society for Neuroscience. Online version.
  7. H. E. Plesser and K. Austvoll.
    Efficient probabilistic wiring of spatial neuronal network using walker's alias method.
    In Proceedings of the Eighth Göttingen Meeting of the German Neuroscience Society, pages 1277 (T26-1C). Neurowissenschaftliche Gesellschaft, 2009. Online version.
  8. H. E. Plesser, K. Austvoll, and E. Nordlie.
    Simulation and visualization of the early visual system using PyNEST and ConnPlotter.
    Scandinavian Journal of Vision Science, 2:9-10, 2009.
    Abstract for Kongsberg Vision Meeting 2009.
  9. M. Diesmann, J. Eppler, M.-O. Gewaltig, A. Morrison, and H. E. Plesser.
    NEST2: A parallel simulator for large neuronal networks.
    In Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2008, page 152, Stockholm, 2008. International Neuroinformatics Coordinating Facility. Online version.
  10. M.-O. Gewaltig, M. Diesmann, H. E. Plesser, and A. Morrison.
    NEST, a parallel and distributed simulator for large networks of spiking neurons.
    In 2008 Neuroscience Meeting Planner, page 694.1, Washington, DC, 2008. Society for Neuroscience.
  11. E. Nordlie, H. E. Plesser, and M.-O. Gewaltig.
    Towards reproducible descriptions of neuronal network models.
    In Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2008., 2008. DOI 10.3389/conf.neuro.11.2008.01.086.
  12. E. Nordlie, H. E. Plesser, G. T. Einevoll, and M.-O. Gewaltig.
    Rate-based and spiking neuron models of the visual thalamocortical pathway: a quantitative comparison.
    In 2007 Neuroscience Meeting Planner, page 392.14, San Diego, CA, 2007. Society for Neuroscience.
  13. J. M. Eppler, A. Morrison, M. Diesmann, H. E. Plesser, and M.-O. Gewaltig.
    Parallel and distributed simulation of large biological neural networks with NEST.
    In CNS*2006 Abstract Book, page 48. Organization for Computational Neurosciences, 2006. Online version.
  14. E. Nordlie, H. E. Plesser, and G. T. Einevoll.
    Effects of cortical feedback on relay neurons in cat lateral geniculate nucleus.
    In Meeting Program, Biofysikk-møtet 2006, 2006.
  15. H. E. Plesser, G. T. Einevoll, E. Nordlie, and M.-O. Gewaltig.
    Thalamocortical responses to compound stimuli: spiking versus rate models.
    In Soc Neurosci Abstr, volume 36, page 241.12, Washington, DC, 2006. Society for Neuroscience.
  16. H. E. Plesser, A. Morrison, S. Straube, and M. Diesmann.
    Precise and efficient discrete time neural network simulation.
    In CNS* 2006 Abstract Book, page 83, 2006. Online version.
  17. G. T. Einevoll, H. E. Plesser, and J. Wyller.
    Physics in the brain.
    In Abstracts of the International Cross-Disciplinary Symposium on Physics and Biology, page 8, Lysebu, Norway, 2005. Centre for Advanced Studies, University of Oslo. Online version.
  18. M.-O. Gewaltig, M. Diesmann, A. Morrison, and H. E. Plesser.
    Aspects of efficient simulation of large heterogenous networks.
    In CNS* 2005 Abstract Book, page 49, 2005. Online version.
  19. A. Morrison, J. Hake, S. Straube, H. E. Plesser, and M. Diesmann.
    Precise spike timing with exact subthreshold integration in discrete time network simulations.
    In H. Zimmermann and K. Kriegelstein, editors, Proceedings of the 6th Meeting of the German Neuroscience Society / 30th Goettingen Neurobiology Conference 2005, page 205B, Berlin, 2005. Neurowissenschaftliche Gesellschaft. Reprint.
  20. H. E. Plesser, G. T. Einevoll, and M.-O. Gewaltig.
    CoThaCo: A comprehensive model of the thalamocortical pathway.
    In CNS* 2005 Abstract Book, page 50, 2005. Online version.
  21. M. Diesmann, M.-O. Gewaltig, A. Morrison, and H. E. Plesser.
    Simulating large neuronal networks with NEST.
    In J. G. Bjaalie, G. T. Einevoll, and J. Hertz, editors, 2nd Nordic Neuroinformatics Workshop: Meeting Abstracts, page 9, 2004. Online version.
  22. H. E. Plesser and G. T. Einevoll.
    Cothaco: A comprehensive model of the thalamocortical pathway.
    In F. Wörgötter, editor, Early Cognitive Vision Workshop: Meeting Abstracts, pages 58-1-58-4. University of Stirling, 2004.
  23. G. T. Einevoll and H. E. Plesser.
    Artificial vision: What can we learn from biology?.
    In B. Tessem, P. Ala-Siuru, P. Doherty, and B. Mayoh, editors, Eighth Scandinavian Conference on Artificial Intelligence, pages 183-188, Amsterdam, 2003. IOS Press.
  24. G. T. Einevoll and H. E. Plesser.
    Extended DOG model for relay cells in cat lateral geniculate nucleus.
    In N. Elsner and H. Zimmermann, editors, Proceedings of the 5th Meeting of the German Neuroscience Society 2003, pages 629-630, Stuttgart, 2003. Thieme.
  25. G. T. Einevoll and H. E. Plesser.
    Extended DOG receptive-field model for LGN relay cells incorporating cortical-feedback effects.
    In Soc Neurosci Abstr, volume 33, page 68.11, Washington, DC, 2003. Society for Neuroscience.
  26. G. T. Einevoll and H. E. Plesser.
    Extended DOG model for receptive fields of relay neurons in cat lateral geniculate nucleus.
    In Abstracts, Fysikermøtet 2003, Oslo, 2003. Norsk Fysisk Selskap.
  27. H. E. Plesser, P. Jurkus, and G. T. Einevoll.
    CoReti: an efficient computational model of retinal processing.
    In Soc Neurosci Abstr, volume 33, page 698.16, Washington, DC, 2003. Society for Neuroscience.
  28. G. T. Einevoll and H. E. Plesser.
    Models of thalamocortical-loop effects on relay cells in dlgn: Suggestions for experiments.
    In Soc Neurosci Abstr, volume 32, page 761.11, Washington, DC, 2002. Society for Neuroscience.
  29. G. T. Einevoll and H. E. Plesser.
    Modelling the early visual pathway.
    In Abstracts, Biofysikermøtet 2002, pages O-8, Trondheim, 2002. Faggruppe for Biofysikk, Norsk Fysisk Selskap.
  30. G. T. Einevoll and H. E. Plesser.
    Mathematical modelling of thalamocortical loop effects on relay-cell responses to drifting gratings.
    In Abstracts, Royal Society Discussion Meeting on The essential role of the thalamus in cortical functioning, London, 2002. Royal Society.
  31. K. Pettersen, H. E. Plesser, and G. T. Einevoll.
    Modelling extracellular field potentials around nerve cells.
    In Abstracts, Biofysikermøtet 2002, pages P-9, Trondheim, 2002. Faggruppe for Biofysikk, Norsk Fysisk Selskap.
  32. H. E. Plesser, V. Strengen, and G. T. Einevoll.
    Contrast-dependence of signal transduction in dLGN.
    In Abstracts, Biofysikermøtet 2002, pages O-9, Trondheim, 2002. Faggruppe for Biofysikk, Norsk Fysisk Selskap.
  33. H. E. Plesser and G. T. Einevoll.
    A network model for studying the consquences of localized and non-localized inhibition of thalamic relay cells.
    In G. Bugmann, editor, 4th Neural Coding Workshop, pages 113-114, Plymouth, 2001.
  34. H. E. Plesser and G. T. Einevoll.
    Spatiotemporal inseparability of thalamic receptive fields due to feedback.
    In Dynamical Neuroscience IX, page 43, San Diego, CA, 2001. NIMH.
  35. H. E. Plesser and G. T. Einevoll.
    Mechanistic models of the visual pathway: A road to better experiments and deeper understanding.
    In Abstracts, Fysikermøtet 2001, pages 45-46, Trondheim, 2001. Norsk Fysisk Selskap.
  36. H. E. Plesser and G. T. Einevoll.
    Simulation of biological neural networks.
    In T. A. Hauge, B. Lie, R. Ergon, M. D. Díez, G.-O. Kaasa, A. Dale, B. Glemmestad, and A. Mjaavatten, editors, Proceedings SIMS 2001, pages 59-69, Linköping, 2001. SIMS.
  37. H. E. Plesser and G. T. Einevoll.
    Mechanistic models of the retinogeniculate transfer function.
    In Soc Neurosci Abstr, volume 31, page 723.13, Washington, DC, 2001. Society for Neuroscience.
  38. H. E. Plesser, G. T. Einevoll, and P. Heggelund.
    Transfer function of relay cells in cat LGN.
    In N. Elsner and G. W. Kreutzberg, editors, Göttingen Neurobiology Report 2001, volume II, page 599, Stuttgart, 2001. Thieme.
  39. H. E. Plesser.
    Noise turns integrate-fire neuron into bandpass filter.
    In N. Elsner and R. Wehner, editors, Göttingen Neurobiology Report 1998, volume II, page 760, Stuttgart, 1998. Thieme.
  40. H. E. Plesser and S. Tanaka.
    Stochastic resonance in a model neuron.
    In N. Elsner and H. Wässle, editors, Göttingen Neurobiology Report 1997, volume II, page 1010, Stuttgart, 1997. Thieme.
  41. H. E. Plesser and D. Wendt.
    A fast algorithm for high-dimensional Markov processes with finite sets of transition rates.
    In Proceedings of the 1996 International Symposium on Nonlinear Theory and its Applications (NOLTA '96), pages 249-252, Kochi, Japan, 1996. Online version.

Papers without Peer Review

  1. H. E. Plesser and K. Pettersen.
    Multilevel models of brain activity: Integrating computational models with experimental evidence.
    Meta, (1):6-11, 2010. Online version.
  2. H. E. Plesser.
    Personnummer og folkeregisteret i dataalderen.
    Lov & Data, (97):1-2, 2009. Reprint.
  3. H. E. Plesser.
    Kartlegging av kameraovervåkning i Oslo.
    Lov & Data, (99):26-27, 2009. Reprint.
  4. G. T. Einevoll, H. E. Plesser, and J. Wyller.
    Simulering av nervesystemer: Biologens hvorfor og matematikerens hvordan.
    NBS-nytt (fagblad for Norsk Biokjemisk Selskap), (1):36-38, 2005.
  5. H. E. Plesser and T. Geisel.
    Signal selection based on stochastic resonance.
    E-print physics/0004019, 2000. Online version.

Software

  1. NEST: The Neural Simulation Toolbox.
    Available at \urlhttp://www.nest-initiative.org. Online version.
  2. H. E. Plesser.
    The ModUhl software collection.
    Technical report, MPI für Strömungsforschung, Göttingen, 2000. More information.
  3. T. Fricke, D. Wendt, and H. E. Plesser.
    Markov classes: Efficient simulation of large stochastic dynamic systems.
    Technical report, RWTH Aachen, Aachen, 1995. More information.

Invited Lectures

  1. H. E. Plesser.
    Visualizing network connectivity with ConnPlotter.
    FACETS CodeJam 3, Freiburg, Germany, 2009-10-08, 2009.
  2. H. E. Plesser.
    Large-scale neuronal network models: Principles and practice.
    Bernstein Tutorial @ CNS*09, Berlin, Germany, 2009-07-18, 2009.
  3. H. E. Plesser.
    Large-scale parallel simulation of neuronal networks.
    Invited lecture, NOTUR2008, Tromsø, Norway, 2008-06-04, 2008.
  4. H. E. Plesser.
    NEST: Introduction and tutorial.
    Lecture, Advanced Course in Computational Neuroscience, Obidos, Portugal, August 2004.
  5. H. E. Plesser.
    Computer simulation of networks of nerve cells in the visual thalamus.
    Invited lecture, Neuroinformatics in Norway, University of Oslo, January 2003.
  6. H. E. Plesser.
    Introduction to mathematical modeling in visual neuroscience & mathematical modeling in neuroscience: Two examples, June 2002.
    Invited lecture, Nordic Summer School on Mathematical Modeling and Analysis of Biological Systems and Processes, Sigtuna, Sweden.
  7. H. E. Plesser.
    Neural signal processing by means of noise?, June 2000.
    Invited lecture, Nordic Symposium on Computational Biology, Sigtuna, Sweden.

Guest Lectures

  1. H. E. Plesser.
    Towards reproducible descriptions of neuronal network models, 2009.
    Lecture, RIKEN Brain Sciences Institute, Wako-shi, Saitama, Japan, August 2009.
  2. H. E. Plesser.
    Simulating neuronal networks with PyNEST.
    Lecture, Institute for Physics, University of Oldenburg, April 2009.
  3. H. E. Plesser.
    Modelling large-scale neuronal networks with the NEST topology module.
    Live Demo, INCF Booth, 39$^th$ Society for Neuroscience Annual Meeting, 2009.
  4. H. E. Plesser, E. Nordlie, and M.-O. Gewaltig.
    Is computational biology a reliable science?.
    Lecture, PSBio2009: Biological Explanation: Systems, Levels, and Causes, Oslo, 2009. Preprint.
  5. H. E. Plesser.
    Parallel simulation of large neuronal networks on clusters of multiprocessor computers.
    Lecture, Simula Research Center, Lysaker, Januar 2008.
  6. H. E. Plesser.
    Parallel simulation of large neuronal networks on clusters of multiprocessor computers.
    Lecture, Sintef IKT, Oslo, Januar 2008.
  7. H. E. Plesser, M. Diesmann, M.-O. Gewaltig, A. Morrison, and A. Aertsen.
    NEST: A simulation tool for large neuronal networks.
    Live Demo, INCF Booth, 36$^\textth$ Annual Meeting of the Society for Neuroscience, Oct 2006. Online version.
  8. H. E. Plesser.
    CoThaCo: A model of the thalamocortical system.
    Lecture, Visual and Computational Neuroscience Seminar, Kongsberg, 2005.
  9. H. E. Plesser, K. Austvoll, and E. Nordlie.
    Simulation and visualization of the early visual system using PyNEST and ConnPlotter.
    Lecture, Visual and Computational Neuroscience Seminar, Kongsberg, 2005-10-11, 2005.
  10. H. E. Plesser.
    CoThaCo: A comprehensive thalamo-cortical network model.
    Lecture, Laboratory for Computational Neuroscience/CNRS, Gif-sur-Yvette, June 2003.
  11. H. E. Plesser.
    Extended DOG model for relay cells in cat lateral geniculate nucleus.
    Lecture, CNRS/Université René Descartes, Paris, June 2003.
  12. H. E. Plesser.
    Extended DOG model for relay cells in cat lateral geniculate nucleus.
    Lecture, Northwestern University, Evanston, IL, September 2002.
  13. H. E. Plesser.
    Stochastic resonance in endogenously and exogenously driven neurons.
    Poster, Physics of Information and Synchronization in Stochastic Dynamics Symposium, Dresden, April 2001.
  14. H. E. Plesser.
    Mechanistic models of the early visual pathway.
    Lecture, Center for Neural Science/New York University, November 2001.
  15. H. E. Plesser.
    Mechanistic models of the early visual pathway.
    Lecture, Center for Applied Mathematics/Mount Sinai School of Medicine, New York, November 2001.
  16. H. E. Plesser.
    Approximations to integrate & fire neuron dynamics with applications to stochastic resonance.
    Lecture, ITB/Humboldt-Universität, Berlin, December 2000.
  17. H. E. Plesser.
    Approximations to integrate & fire neuron dynamics with applications to stochastic resonance.
    Lecture, MANTRA/EPFL, Lausanne, December 2000.
  18. H. E. Plesser.
    Approximations to integrate & fire neuron dynamics with applications to stochastic resonance.
    Lecture, MPI for Mathematics in the Sciences, Leipzig, December 2000.

News Items

  1. H. E. Plesser.
    Er elektronisk valg trygg?.
    Leserinnlegg, Klassekampen 2010-02-03, 2010. Reprint.
  2. P. Hellesnes.
    Tusen øyne ser på deg.
    Klassekampen 2008-12-18, 2008. Online version.
    Newspaper article about student project initiated by me.
  3. H. E. Plesser.
    Utrygge fødselsnummer.
    Leserinnlegg, Dagsavisen 2008-10-09, 2008. Online version.
  4. P. Turkerud.
    Tusen øyner ser deg.
    NRK Østlandssendingen 2008-12-18, 2008.
    Radio interview about student project initiated by me.
  5. H. E. Plesser.
    Hvem er naiv?.
    Leserinnlegg, Aftenposten 2005-09-22, 2005. Online version.
  6. G. R. Larsen.
    Forsker-jubel for ny "superregnemaskin".
    Østlandets Blad, p. 10, 2. december, 2003.
  7. E. J. Straumsvåg.
    Ikke mobb roboten min.
    Interview with H. E. Plesser, published on forskning.no, April 2003. Online version.

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