Hans Ekkehard Plesser: Publications

Peer-reviewed journal papers

  1. S. M. Crook, A. P. Davison, R. A. McDougal, and H. E. Plesser.
    Editorial: Reproducibility and rigour in computational neuroscience.
    Frontiers in Neuroinformatics, 14:23, 2020.
    ISSN 1662-5196. DOI 10.3389/fninf.2020.00023.
  2. G. T. Einevoll, A. Destexhe, M. Diesmann, S. Grün, V. Jirsa, M. d Kamps, M. Migliore, T. V. Ness, H. E. Plesser, and F. Schürmann.
    The scientific case for brain simulations.
    Neuron, 102(4):735-744, 2019. DOI 10.1016/j.neuron.2019.03.027. On arXiv.org.
  3. T. Heiberg, B. Kriener, T. Tetzlaff, G. T. Einevoll, and H. E. Plesser.
    Firing-rate model for neurons with a broad repertoire of spiking behaviors.
    J Comput Neurosci, 45:103-132, 2018. DOI 10.1007/s10827-018-0693-9.
  4. H. E. Plesser.
    Reproducibility vs. replicability: A brief history of a confused terminology.
    Frontiers in Neuroinformatics, 11:76, 2018. DOI 10.3389/fninf.2017.00076.
  5. T. Ippen, J. M. Eppler, H. E. Plesser, and M. Diesmann.
    Constructing neuronal network models in massively parallel environments.
    Front. Neuroinform., 11:30, 2017. DOI 10.3389/fninf.2017.00030.
  6. P. Martínez-Cañada, C. Morillas, H. E. Plesser, S. Romero, and F. Pelayo.
    Genetic algorithm for optimization of models of the early stages in the visual system.
    Neurocomputing, 250:101-108, 2017. DOI 10.1016/j.neucom.2016.08.120.
  7. N. P. Rougier, K. Hinsen, F. Alexandre, T. Arildsen, L. A. Barba, F. C. Benureau, C. T. Brown, P. d Buyl, O. Caglayan, A. P. Davison, M.-A. Delsuc, G. Detorakis, A. K. Diem, D. Drix, P. Enel, B. Girard, O. Guest, M. G. Hall, R. N. Henriques, X. Hinaut, K. S. Jaron, M. Khamassi, A. Klein, T. Manninen, P. Marchesi, D. McGlinn, C. Metzner, O. Petchey, H. E. Plesser, T. Poisot, K. Ram, Y. Ram, E. Roesch, C. Rossant, V. Rostami, A. Shifman, J. Stachelek, M. Stimberg, F. Stollmeier, F. Vaggi, G. Viejo, J. Vitay, A. E. Vostinar, R. Yurchak, and T. Zito.
    Sustainable computational science: the ReScience initiative.
    PeerJ Computer Science, 3:e142, 2017. DOI 10.7717/peerj-cs.142.
  8. B. Kriener, H. Enger, T. Tetzlaff, H. E. Plesser, M.-O. Gewaltig, and G. T. Einevoll.
    Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses..
    Front Comput Neurosci, 8:136, 2014. DOI 10.3389/fncom.2014.00136.
  9. S. Kunkel, M. Schmidt, J. M. Eppler, H. E. Plesser, G. Masumoto, J. Igarashi, S. Ishii, T. Fukai, A. Morrison, M. Diesmann, and M. Helias.
    Spiking network simulation code for petascale computers..
    Front Neuroinform, 8:78, 2014. DOI 10.3389/fninf.2014.00078.
  10. T. Heiberg, B. Kriener, T. Tetzlaff, A. Casti, G. T. Einevoll, and H. E. Plesser.
    Firing-rate models capture essential response dynamics of LGN relay cells..
    J Comput Neurosci, 35:359-375, 2013. DOI 10.1007/s10827-013-0456-6.
  11. S. Crook, J. Bednar, S. Berger, R. Cannon, A. Davison, M. Djurfeldt, J. Eppler, B. Kriener, S. Furber, B. Graham, H. E. Plesser, L. Schwabe, L. Smith, V. Steuber, and S. v Albada.
    Creating, documenting and sharing network models.
    Network-Comp Neural, 23:131-149, 2012. Online version. Preprint.
  12. G. T. Einevoll and H. E. Plesser.
    Extended difference-of-gaussians model incorporating cortical feedback for relay cells in the lateral geniculate nucleus of cat.
    Cogn Neurodyn, 6:307-324, 2012. DOI 10.1007/s11571-011-9183-8.
  13. S. Kunkel, T. C. Potjans, J. M. Eppler, H. E. Plesser, A. Morrison, and M. Diesmann.
    Meeting the memory challenges of brain-scale network simulation.
    Front. Neuroinform., 5:35, 2012. DOI 10.3389/fninf.2011.00035.
  14. 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.
  15. H. E. Plesser and A. G. Jahnsen.
    Re-seeding invalidates tests of random number generators.
    Appl Math and Comput, 217:339-346, 2010. DOI 10.1016/j.amc.2010.05.066. Preprint.
  16. E. Nordlie, M.-O. Gewaltig, and H. E. Plesser.
    Towards reproducible descriptions of neuronal network models.
    PLoS Comput Biol, 5(8):e1000456, 2009. DOI 10.1371/journal.pcbi.1000456.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. H. E. Plesser and T. Geisel.
    Stochastic resonance in neuron models: Endogenous stimulation revisited.
    Phys Rev E, 63:031916-1-6, 2001. Reprint.
  22. 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.
  23. 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.
  24. 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. DOI 10.1016/S0925-2312(02)00499-X.
  3. H. E. Plesser and T. Geisel.
    Signal processing by means of noise.
    Neurocomputing, 38-40:307-312, 2001. DOI 10.1016/S0925-2312(01)00459-3.
  4. H. E. Plesser and W. Gerstner.
    Escape rate models for noisy integrate-and-fire neurons.
    Neurocomputing, 32-33:219-224, 2000. DOI 10.1016/S0925-2312(00)00167-3.
  5. H. E. Plesser and T. Geisel.
    Bandpass properties of integrate-fire neurons.
    Neurocomputing, 26-27:229-235, 1999. DOI 10.1016/S0925-2312(99)00076-4.

Book chapters

  1. H. E. Plesser, M. Diesmann, M.-O. Gewaltig, and A. Morrison.
    NEST: the Neural Simulation Tool.
    In D. Jaeger and R. Jung, editors, Encyclopedia of Computational Neuroscience. Springer New York, New York, NY, 2019. DOI 10.1007/978-1-4614-7320-6_258-6.
  2. H. E. Plesser, M. Diesmann, M.-O. Gewaltig, and A. Morrison.
    NEST: the Neural Simulation Tool.
    In D. Jaeger and R. Jung, editors, Encyclopedia of Computational Neuroscience. Springer, Berlin Heidelberg, 2015. DOI 10.1007/978-1-4614-6675-8_258.
  3. S. Crook, A. P. Davison, and H. E. Plesser.
    Learning from the past: Approaches for reproducibility in computational neuroscience.
    In J. M. Bower, editor, 20 Years in Computational Neuroscience, chapter 4, pages 73-102. Springer Science+Business Media, New York, 2013. DOI 10.1007/978-1-4614-1424-7_4.
  4. M.-O. Gewaltig, A. Morrison, and H. E. Plesser.
    NEST by example: An introduction to the neural simulation tool NEST.
    In N. Le Novère, editor, Computational Systems Neurobiology, chapter 18, pages 533-558. Springer Science+Business Media, Dordrecht, 2012. DOI 10.1007/978-94-007-3858-4_18. Preprint.
  5. H. E. Plesser.
    Generating random numbers.
    In S. Grün and S. Rotter, editors, Analysis of Parallel Spike Trains, Springer Series in Computational Neuroscience, chapter 19, pages 399-411. Springer, New York, 2010.

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. R. Helin, S. Essink, H. Bos, E. Hagen, M. Helias, J. Senk, T. Tetzlaff, S. J. v Alabada, M. Diesmann, S. Grün, and H. E. Plesser.
    Conditions for and detectability of extremely fast oscillations in neuronal activity.
    In 2019 Neuroscience Meeting Planner, page Program no. 464.05, Chicago, IL, 2019. Society for Neuroscience. Online version. Reprint.
  2. H. Mørk, S. B. Vennemo, and H. E. Plesser.
    NEST 3 quick preview.
    In NEST Conference 2019 Abstracts, Ås, Norway, 2019.
  3. Ø. W. Gregersen, G. Ø. Kløkstad, S. Hervik, H. E. Plesser, and I. Pettersen.
    Some factors affecting the grades of technology students.
    Nordic Journal of STEM Education, 1:167-173, 2017. DOI 10.5324/njsteme.v1i1.2248.
  4. H. Mørk, S. B. Vennemo, and H. E. Plesser.
    Instrumenting network simulations with the NESTConnectionApp.
    In Bernstein Conference 2017 Abstracts, Göttingen, 2017. DOI 10.12751/nncn.bc2017.0128.
  5. A. Sevenius Nilsen, R. Murphy, B. E. Juel, H. E. Plesser, S. Hill, T. Nieus, M. Massimini, and J. F. Storm.
    Simulating deep sleep and awake states in a mammalian thalamocortical model.
    In The Nordic Neuroscience 2017 Abstract Book, page 29, Stockholm, 2017. Scandinavian Physiological Society. Online version.
  6. T. Ippen, J. M. Eppler, M. Diesmann, and H. E. Plesser.
    Massively parallel neuronal network model construction.
    In The Nordic Neuroscience 2015 Conference Book, page 145, Trondheim, 2015. Scandinavian Physiological Society. Online version.
  7. T. Heiberg and H. E. Plesser.
    A pythonic workflow for automated large-scale parameter scans.
    In Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2013, page 190, Stockholm, 2013. International Neuroinformatics Coordinating Facility. Online version.
  8. T. Heiberg, B. Kriener, T. Tetzlaff, G. T. Einevoll, and H. E. Plesser.
    Firing-rate models for neurons with a broad repertoire of spiking behaviors.
    BMC Neuroscience, 14(Suppl 1):P317, 2013. DOI 10.1186/1471-2202-14-S1-P317.
  9. D. Hjertholm, B. Kriener, and H. E. Plesser.
    A Python test suite for statistical properties of probabilistic networks with and without spatial structure.
    In Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2013, page P79, Stockholm, 2013. International Neuroinformatics Coordinating Facility. Online version.
  10. B. Kriener, H. Enger, T. Tetzlaff, H. E. Plesser, M.-O. Gewaltig, and G. T. Einevoll.
    Dynamics and lifetime of persistent activity states in random networks of spiking neurons with strong synapses.
    BMC Neuroscience, 14(Suppl 1):P121, 2013. Online version.
  11. S. Kunkel, M. Schmidt, J. M. Eppler, H. E. Plesser, J. Igarashi, G. Masumoto, T. Fukai, S. Ishii, A. Morrison, M. Diesmann, and M. Helias.
    From laptops to supercomputers: a single highly scalable code base for spiking neuronal network simulations.
    BMC Neuroscience, 14(Suppl 1):P163, 2013. DOI 10.1186/1471-2202-14-S1-P163.
  12. H. E. Plesser, J. M. Eppler, and M.-O. Gewaltig.
    20 years of NEST: A mature brain simulator.
    In Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2013, page 227, Stockholm, 2013. International Neuroinformatics Coordinating Facility. Online version.
  13. T. Heiberg, B. Kriener, T. Tetzlaff, A. Casti, G. T. Einevoll, and H. E. Plesser.
    Firing-rate models for the retina-LGN connection derived from experiments.
    In Neuroscience Meeting Planner, New Orleans, LA, 2012. Society for Neuroscience. Online version.
  14. S. Kunkel, M. Helias, T. C. Potjans, J. M. Eppler, H. E. Plesser, and M. Diesmann.
    Memory consumption of neuronal network simulators at the brain scale.
    In K. Binder, G. Münster, and M. Kremer, editors, NIC Symposium 2012--Proceedings, volume 45 of NIC Series, pages 81-88, Jülich, 2012. Forschungszentrum Jülich. Online version.
  15. J. M. Eppler, H. Enger, T. Heiberg, B. Kriener, H. E. Plesser, M. Diesmann, and M. Djurfeldt.
    Evaluating the connection-set algebra for the neural simulator NEST.
    In Neuroinformatics 2011 Abstract Book, page 286, Stockholm, 2011. INCF. Online version.
  16. A. Gorchetchnikov, R. Cannon, R. Clewley, H. Cornelis, A. Davison, E. D. Schutter, M. Djurfeldt, P. Gleeson, S. Hill, M. Hines, B. Kriener, Y. L. Franc, C.-C. Lo, A. Morrison, E. Muller, H. E. Plesser, I. Raikov, S. Ray, L. Schwabe, and B. Szatmary.
    NineML: declarative, mathematically-explicit descriptions of spiking neuronal networks.
    In Neuroinformatics 2011 Abstract Book, page 98, Stockholm, 2011. INCF. Online version.
  17. T. Heiberg, T. Tetzlaff, B. Kriener, H. E. Plesser, and G. T. Einevoll.
    Rate dynamics of the retina-LGN connection.
    BMC Neuroscience, 12(Suppl 1):P90, 2011. DOI 10.1186/1471-2202-12-S1-P90.
  18. H. E. Plesser and J. M. Eppler.
    Flexible and efficient recording of neuronal properties in large network simulations: The NEST multimeter.
    BMC Neuroscience, 12(Suppl 1):P92, 2011. DOI 10.1186/1471-2202-12-S1-P92.
  19. H. E. Plesser, S. Crook, and A. Davison.
    Reproducible models and reliable simulations: Current trends in computational neuroscience.
    In SIAM Computational Science and Engineering 2011 Final Program and Abstracts, page 226, Reno, NV, 2011. Society for Industrial and Applied Mathematics. Online version. Reprint.
  20. I. Raikov, R. Cannon, R. Clewley, H. Cornelis, A. Davison, E. D. Schutter, M. Djurfeldt, P. Gleeson, A. Gorchetchnikov, H. E. Plesser, S. Hill, M. Hines, B. Kriener, Y. L. Franc, C.-C. Lo, A. Morrison, E. Muller, S. Ray, L. Schwabe, and B. Szatmary.
    NineML: the network interchange for neuroscience modeling language.
    BMC Neuroscience, 12(Suppl 1):P330, 2011. DOI 10.1186/1471-2202-12-S1-P330.
  21. M.-O. Gewaltig, M. Diesmann, J. M. Eppler, M. Helias, A. Morrison, and H. E. Plesser.
    NEST 2: a parallel simulator for large scale neuronal simulations.
    In 2010 Neuroscience Meeting Planner, page Program no. 208.28, San Diego, CA, 2010. Society for Neuroscience.
  22. 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.
  23. T. C. Potjans, S. Kunkel, A. Morrison, H. E. Plesser, and M. Diesmann.
    Simulating neuronal networks at the brain scale on BlueGene/P supercomputers with NEST.
    In 2010 Neuroscience Meeting Planner, page Program no. 208.29, San Diego, CA, 2010. Society for Neuroscience.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.
  40. 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.
  41. 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.
  42. 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.
  43. 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.
  44. 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.
  45. 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.
  46. 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.
  47. 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.
  48. 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.
  49. 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.
  50. 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.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. 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.
  58. 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.
  59. 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.
  60. 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.
  61. 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.
  62. 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.
  63. 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 H. Enger.
    NEST Topology User Manual, 2013.
  2. H. E. Plesser and K. Pettersen.
    Multilevel models of brain activity: Integrating computational models with experimental evidence.
    Meta, (1):6-11, 2010. Online version.
  3. H. E. Plesser.
    Personnummer og folkeregisteret i dataalderen.
    Lov & Data, (97):1-2, 2009. Reprint.
  4. H. E. Plesser.
    Kartlegging av kameraovervåkning i Oslo.
    Lov & Data, (99):26-27, 2009. Reprint.
  5. 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.
  6. H. E. Plesser and T. Geisel.
    Signal selection based on stochastic resonance.
    E-print physics/0004019, 2000. Online version.

Software

  1. J. Jordan, H. Mørk, S. B. Vennemo, D. Terhorst, A. Peyser, T. Ippen, R. Deepu, J. M. Eppler, A. v Meegen, S. Kunkel, A. Sinha, T. Fardet, S. Diaz, A. Morrison, W. Schenck, D. Dahmen, J. Pronold, J. Stapmanns, G. Trensch, S. Spreizer, J. Mitchell, S. Graber, J. Senk, C. Linssen, J. Hahne, A. Serenko, D. Naoumenko, E. Thomson, I. Kitayama, S. Berns, and H. E. Plesser.
    NEST 2.18.0, June 2019. More information.
  2. C. Linssen, M. E. Lepperød, J. Mitchell, J. Pronold, J. M. Eppler, C. Keup, A. Peyser, S. Kunkel, P. Weidel, Y. Nodem, D. Terhorst, R. Deepu, M. Deger, J. Hahne, A. Sinha, A. Antonietti, M. Schmidt, L. Paz, J. Garrido, T. Ippen, L. Riquelme, A. Serenko, T. Kühn, I. Kitayama, H. Mørk, S. Spreizer, J. Jordan, J. Krishnan, M. Senden, E. Hagen, A. Shusharin, S. B. Vennemo, D. Rodarie, A. Morrison, S. Graber, J. Schuecker, S. Diaz, B. Zajzon, and H. E. Plesser.
    NEST 2.16.0, August 2018. More information.
  3. S. Kunkel, A. Morrison, P. Weidel, J. M. Eppler, A. Sinha, W. Schenck, M. Schmidt, S. B. Vennemo, J. Jordan, A. Peyser, D. Plotnikov, S. Graber, T. Fardet, D. Terhorst, H. Mørk, G. Trensch, A. Seeholzer, R. Deepu, J. Hahne, I. Blundell, T. Ippen, J. Schuecker, H. Bos, S. Diaz, E. Hagen, S. Mahmoudian, C. Bachmann, M. E. Lepperød, O. Breitwieser, B. Golosio, H. Rothe, H. Setareh, M. Djurfeldt, T. Schumann, A. Shusharin, J. Garrido, E. B. Muller, A. Rao, J. H. Vieites, and H. E. Plesser.
    Nest 2.12.0, March 2017. More information.
  4. A. Peyser, A. Sinha, S. B. Vennemo, T. Ippen, J. Jordan, S. Graber, A. Morrison, G. Trensch, T. Fardet, H. Mørk, J. Hahne, J. Schuecker, M. Schmidt, S. Kunkel, D. Dahmen, J. M. Eppler, S. Diaz, D. Terhorst, R. Deepu, P. Weidel, I. Kitayama, S. Mahmoudian, D. Kappel, M. Schulze, S. Appukuttan, T. Schumann, H. C. Tunç, J. Mitchell, M. Hoff, E. Müller, M. M. Carvalho, B. Zajzon, and H. E. Plesser.
    NEST 2.14.0, October 2017. More information.
  5. H. Bos, A. Morrison, A. Peyser, J. Hahne, M. Helias, S. Kunkel, T. Ippen, J. M. Eppler, M. Schmidt, A. Seeholzer, M. Djurfeldt, S. Diaz, J. Morén, R. Deepu, T. Stocco, M. Deger, F. Michler, and H. E. Plesser.
    Nest 2.10.0, December 2015. More information.
  6. J. M. Eppler, R. Pauli, A. Peyser, T. Ippen, A. Morrison, J. Senk, W. Schenck, H. Bos, M. Helias, M. Schmidt, S. Kunkel, J. Jordan, M.-O. Gewaltig, C. Bachmann, J. Schuecker, S. Albada, T. Zito, M. Deger, F. Michler, E. Hagen, H. Setareh, L. Riquelme, A. Shirvani, R. Duarte, R. Deepu, and H. E. Plesser.
    Nest 2.8.0, September 2015. More information.
  7. NEST.
    NEST: The Neural Simulation Toolbox, 2004. More information.
  8. H. E. Plesser.
    The ModUhl software collection.
    Technical report, MPI für Strömungsforschung, Göttingen, 2000. More information.
  9. 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.
    Network simulation with NEST.
    Guest lecture, SP3 Workshop at HBP Summit 2016, Florence, Italy, 2016-10-12, 2016.
  2. H. E. Plesser.
    Network simulation with NEST.
    Guest lecture, Swammerdam Institute for Life Sciences, University of Amsterdam, The Netherlands, 2016-10-10, 2016.
  3. H. E. Plesser.
    NEST: A simulator for the brain scale.
    Invited lecture, Center for Integrative Neuroplasticity, University of Oslo, Norway, 2014-11-14, 2014.
  4. H. E. Plesser.
    Taking neuronal network simulation to the brain scale.
    Invited lecture, NOTUR2012, Tromsø, Norway, 2012-06-15, 2012.
  5. H. E. Plesser.
    Visualizing network connectivity with ConnPlotter.
    FACETS CodeJam 3, Freiburg, Germany, 2009-10-08, 2009.
  6. H. E. Plesser.
    Large-scale neuronal network models: Principles and practice.
    Bernstein Tutorial @ CNS*09, Berlin, Germany, 2009-07-18, 2009.
  7. H. E. Plesser.
    Large-scale parallel simulation of neuronal networks.
    Invited lecture, NOTUR2008, Tromsø, Norway, 2008-06-04, 2008.
  8. H. E. Plesser.
    NEST: Introduction and tutorial.
    Lecture, Advanced Course in Computational Neuroscience, Obidos, Portugal, August 2004.
  9. H. E. Plesser.
    Computer simulation of networks of nerve cells in the visual thalamus.
    Invited lecture, Neuroinformatics in Norway, University of Oslo, January 2003.
  10. 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.
  11. 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.
    Brain simulation technology for peta- and exascale systems: Experiences with the NEST simulator.
    Lecture, Simula Research Laboratory, 2017-05-10, 2017.
  2. S. Kunkel and H. E. Plesser.
    NEST: Current developments.
    Lecture, NEST User Workshop 2016, Karlsruhe, Germany, 2016-11-03, 2016.
  3. H. E. Plesser.
    NEST, HBP, & Large-Scale Simulation.
    Seminar lecture, Center for Integrative Neuroplasticity, University of Oslo, Norway, 2016-08-31, 2016.
  4. H. E. Plesser.
    The Human Brain Project Research Infrastructure.
    Technologies for Digital Life Workshop, Centre for Digial Life Norway, Bergen, Norway, 2016-10-21, 2016.
  5. H. E. Plesser.
    Network simulation with NEST.
    Lecture, Special Session on NEST at HBP Summit 2016, Florence, Italy, 2016-10-13, 2016.
  6. H. E. Plesser.
    Towards reproducible descriptions of neuronal network models, 2009.
    Lecture, RIKEN Brain Sciences Institute, Wako-shi, Saitama, Japan, August 2009.
  7. H. E. Plesser.
    Simulating neuronal networks with PyNEST.
    Lecture, Institute for Physics, University of Oldenburg, April 2009.
  8. 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.
  9. 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.
  10. H. E. Plesser.
    Parallel simulation of large neuronal networks on clusters of multiprocessor computers.
    Lecture, Simula Research Center, Lysaker, Januar 2008.
  11. H. E. Plesser.
    Parallel simulation of large neuronal networks on clusters of multiprocessor computers.
    Lecture, Sintef IKT, Oslo, Januar 2008.
  12. 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.
  13. H. E. Plesser.
    CoThaCo: A model of the thalamocortical system.
    Lecture, Visual and Computational Neuroscience Seminar, Kongsberg, 2005.
  14. 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.
  15. H. E. Plesser.
    CoThaCo: A comprehensive thalamo-cortical network model.
    Lecture, Laboratory for Computational Neuroscience/CNRS, Gif-sur-Yvette, June 2003.
  16. H. E. Plesser.
    Extended DOG model for relay cells in cat lateral geniculate nucleus.
    Lecture, CNRS/Université René Descartes, Paris, June 2003.
  17. H. E. Plesser.
    Extended DOG model for relay cells in cat lateral geniculate nucleus.
    Lecture, Northwestern University, Evanston, IL, September 2002.
  18. H. E. Plesser.
    Stochastic resonance in endogenously and exogenously driven neurons.
    Poster, Physics of Information and Synchronization in Stochastic Dynamics Symposium, Dresden, April 2001.
  19. H. E. Plesser.
    Mechanistic models of the early visual pathway.
    Lecture, Center for Neural Science/New York University, November 2001.
  20. H. E. Plesser.
    Mechanistic models of the early visual pathway.
    Lecture, Center for Applied Mathematics/Mount Sinai School of Medicine, New York, November 2001.
  21. H. E. Plesser.
    Approximations to integrate & fire neuron dynamics with applications to stochastic resonance.
    Lecture, ITB/Humboldt-Universität, Berlin, December 2000.
  22. H. E. Plesser.
    Approximations to integrate & fire neuron dynamics with applications to stochastic resonance.
    Lecture, MANTRA/EPFL, Lausanne, December 2000.
  23. 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. G. Grah.
    Nest::documented.
    Interviewed in movie about the NEST Simulator, July 2012. Online version.
  2. G. Grah.
    Nest--a brain simulator.
    Interviewed in movie about the NEST Simulator, July 2012. Online version.
  3. H. E. Plesser.
    Er elektronisk valg trygg?.
    Leserinnlegg, Klassekampen 2010-02-03, 2010. Reprint.
  4. P. Hellesnes.
    Tusen øyne ser på deg.
    Klassekampen 2008-12-18, 2008. Online version.
    Newspaper article about student project initiated by me.
  5. H. E. Plesser.
    Utrygge fødselsnummer.
    Leserinnlegg, Dagsavisen 2008-10-09, 2008. Online version.
  6. P. Turkerud.
    Tusen øyner ser deg.
    NRK Østlandssendingen 2008-12-18, 2008.
    Radio interview about student project initiated by me.
  7. H. E. Plesser.
    Hvem er naiv?.
    Leserinnlegg, Aftenposten 2005-09-22, 2005. Online version.
  8. G. R. Larsen.
    Forsker-jubel for ny "superregnemaskin".
    Østlandets Blad, p. 10, 2. december, 2003.
  9. E. J. Straumsvåg.
    Ikke mobb roboten min.
    Interview with H. E. Plesser, published on forskning.no, April 2003. Online version.

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