Synonyms
Definition
NEST, the Neural Simulation Tool, is optimized for large networks of spiking model neurons. NEST includes a wide range of neuron and synapse models and provides high-level commands to create spatially structured networks. NEST is controlled through a Python-based interface and supports parallel simulation. NEST is available from www.nest-simulator.org under a GNU Public License.
Detailed Description
NEST is optimized for networks of neurons whose subthreshold dynamics can be described by a small number of differential equations. By default, NEST simulations operate on a fixed time grid. However, NEST also supports precisely timed spikes (Morrison et al. 2007b; Krishnan et al. 2018), combining the precision of event-driven simulators (Henker et al. 2012) with the efficiency of grid-based simulation. Furthermore, NEST allows the simulation of neurons coupled by gap junctions (Hahne et al. 2015) and of networks of rate-based neurons...
References
Davison A, Brüderle D, Eppler J, Kremkow J, Muller E, Pecevski D, Perrinet L, Yger P (2008) PyNN: a common interface for neuronal network simulators. Front Neuroinform 2(11). https://doi.org/10.3389/neuro.11.011.2008
Diesmann M, Gewaltig MO, Aertsen A (1995) SYNOD: an environment for neural systems simulations. language interface and tutorial. Tech. Rep. GC-AA-/95-3, The Weizmann Institute of Science, The Grodetsky Center for Research of Higher Brain Functions, Weizmann Institute of Science, Israel
Djurfeldt M, Hjorth J, Eppler JM, Dudani N, Helias M, Potjans TC, Bhalla US, Diesmann M, Kotaleski JH, Ekeberg O (2010) Run-time interoperability between neuronal network simulators based on the music framework. Neuroinformatics 8(1):43–60. https://doi.org/10.1007/s12021-010-9064-z
Eppler JM, Helias M, Muller E, Diesmann M, Gewaltig MO (2008) PyNEST: a convenient interface to the NEST simulator. Front Neuroinform 2(12). https://doi.org/10.3389/neuro.11.012.2008
Eppler JM, Kupper R, Plesser HE, Diesmann M (2009) A testsuite for a neural simulation engine. In: Frontiers in neuroinformatics. Conference abstract: 2nd INCF Congress of Neuroinformatics. International Neuroinformatics Coordinating Facility, Plzen. https://doi.org/10.3389/conf.neuro.11.2009.08.042
Gewaltig MO, Morrison A, Plesser HE (2012) NEST by example: an introduction to the neural simulation tool NEST. In: Le Novère N (ed) Computational systems neurobiology, Springer Science+Business Media, Dordrecht, Chap. 18, pp 533–558, https://doi.org/10.1007/978-94-007-3858-418
Hahne J, Helias M, Kunkel S, Igarashi J, Bolten M, Frommer A, Diesmann M (2015) A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations. Front Neuroinform 9(22). https://doi.org/10.3389/fninf.2015.00022
Hahne J, Dahmen D, Schuecker J, Frommer A, Bolten M, Helias M, Diesmann M (2017) Integration of continuous-time dynamics in a spiking neural network simulator. Front Neuroinform 11(34). https://doi.org/10.3389/fninf.2017.00034
Henker S, Partzsch J, Schüffny R (2012) Accuracy evaluation of numerical methods used in state-of-the-art simulators for spiking neural networks. J Comput Neurosci 32:309–326. https://doi.org/10.1007/s10827-011-0353-9
Jordan J, Ippen T, Helias M, Kitayama I, Sato M, Igarashi J, Diesmann M, Kunkel S (2018) Extremely scalable spiking neuronal network simulation code: from laptops to exascale computers. Front Neuroinform 12(2). https://doi.org/10.3389/fninf.2018.00002
Krishnan J, Mana PP, Helias M, Diesmann M, Napoli ED (2018) Perfect detection of spikes in the linear sub-threshold dynamics of point neurons. Front Neuroinform 11(75). https://doi.org/10.3389/fninf.2017.00075
Kunkel S, Eppler JM, Plesser HE, Gewaltig MO, Diesmann M, Morrison A (2010) NEST: science-driven development of neuronal network simulation software. In: Frontiers in Neuroscience. Conference Abstract: Neuroinformatics 2010, https://doi.org/10.3389/conf.fnins.2010.13.00105
Kunkel S, Schmidt M, Eppler JM, Plesser HE, Masumoto G, Igarashi J, Ishii S, Fukai T, Morrison A, Diesmann M, Helias M (2014) Spiking network simulation code for petascale computers. Front Neuroinform 8(78). https://doi.org/10.3389/fninf.2014.00078
Morrison A, Mehring C, Geisel T, Aertsen A, Diesmann M (2005) Advancing the boundaries of high connectivity network simulation with distributed computing. Neural Comput 17:1776–1801
Morrison A, Aertsen A, Diesmann M (2007a) Spike-time dependent plasticity in balanced recurrent networks. Neural Comput 19:1437–1467
Morrison A, Straube S, Plesser HE, Diesmann M (2007b) Exact subthreshold integration with continuous spike times in discrete time neural network simulations. Neural Comput 19:47–79
Plesser HE, Enger H (2013) NEST topology user manual
Plesser HE, Eppler JM, Morrison A, Diesmann M, Gewaltig MO (2007) Efficient parallel simulation of large-scale neuronal networks on clusters of multiprocessor computers. In: Kermarrec AM, Bougé L, Priol T (eds) Euro-Par 2007: parallel processing, Lecture notes in computer science, vol 4641. Springer-Verlag, Berlin, pp 672–681. https://doi.org/10.1007/978-3-540-74466-5
Potjans W, Morrison A, Diesmann M (2010) Enabling functional neural circuit simulations with distributed computing of neuromodulated plasticity. Front Comput Neurosci 4:141. https://doi.org/10.3389/fncom.2010.0014
Rotter S, Diesmann M (1999) Exact digital simulation of time-invariant linear systems with applications to neuronal modeling. Biol Cybern 81:381–402
Zaytsev YV, Morrison A (2013) Increasing quality and managing complexity in neuroinformatics software development with continuous integration. Front Neuroinform 6(31). https://doi.org/10.3389/fninf.2012.00031
Zaytsev YV, Morrison A (2014) CyNEST: a maintainable Cython-based interface for the NEST simulator. Front Neuroinform 8(23). https://doi.org/10.3389/fninf.2014.00023
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2019 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Plesser, H.E., Diesmann, M., Gewaltig, MO., Morrison, A. (2019). NEST: The Neural Simulation Tool. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_258-6
Download citation
DOI: https://doi.org/10.1007/978-1-4614-7320-6_258-6
Received:
Accepted:
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-7320-6
Online ISBN: 978-1-4614-7320-6
eBook Packages: Living Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences
Publish with us
Chapter history
-
Latest
NEST: The Neural Simulation Tool- Published:
- 29 October 2018
DOI: https://doi.org/10.1007/978-1-4614-7320-6_258-6
-
Original
NEST: The Neural Simulation Tool- Published:
- 18 April 2014
DOI: https://doi.org/10.1007/978-1-4614-7320-6_258-5