Simulation of networks of spiking neurons: A review of tools and strategies

Autor: Andrew P. Davison, Alain Destexhe, Olivier Rochel, Abigail Morrison, Anders Lansner, Dejan Pecevski, Milind Zirpe, Mikael Djurfeldt, Frederick C. Harris, Michelle Rudolph, Philip H. Goodman, Thomas Natschläger, G. Bard Ermentrout, Michael L. Hines, Eilif Muller, Ted Carnevale, Sami El Boustani, Romain Brette, David Beeman, Thierry Viéville, James M. Bower, Markus Diesmann
Přispěvatelé: Département d'informatique - ENS Paris (DI-ENS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Unité de neurosciences intégratives et computationnelles (UNIC), Centre National de la Recherche Scientifique (CNRS), Institut de Neurobiologie Alfred Fessard (INAF), Yale University [New Haven], University of Colorado [Boulder], University of Texas Health Science Center, The University of Texas Health Science Center at Houston (UTHealth), Bernstein Center Freiburg (BCF), Albert-Ludwigs-Universität Freiburg, RIKEN Center for Brain Science [Wako] (RIKEN CBS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Brain Laboratory [Reno], University of Nevada [Reno], Software Competence Center Hagenberg (SCCH), Johannes Kepler Universität Linz (JKU), Graz University of Technology [Graz] (TU Graz), Department of Computer Science - University of Pittsburgh, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Department of Speech, Music and Hearing [KTH Stockholm] (KTH TMH), Royal Institute of Technology [Stockholm] (KTH ), School of Computing [Leeds], University of Leeds, Computer and biological vision (ODYSSEE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-École des Ponts ParisTech (ENPC), Kirchhoff Institut für Physik, Universität Heidelberg [Heidelberg], Département d'informatique de l'École normale supérieure (DI-ENS), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Universität Heidelberg [Heidelberg] = Heidelberg University
Rok vydání: 2007
Předmět:
Computer science
Cognitive Neuroscience
Models
Neurological
02 engineering and technology
Machine learning
computer.software_genre
Article
Task (project management)
Set (abstract data type)
03 medical and health sciences
Cellular and Molecular Neuroscience
0302 clinical medicine
Resource (project management)
Software
0202 electrical engineering
electronic engineering
information engineering
Animals
Humans
Computer Simulation
Neurons
Spiking neural network
Quantitative Biology::Neurons and Cognition
business.industry
Sensory Systems
Electrophysiology
Open source
Quantitative Biology - Neurons and Cognition
FOS: Biological sciences
Synapses
Theory of computation
Benchmark (computing)
[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Neurons and Cognition (q-bio.NC)
020201 artificial intelligence & image processing
Artificial intelligence
Nerve Net
business
computer
Algorithms
030217 neurology & neurosurgery
Zdroj: Journal of Computational Neuroscience
Journal of Computational Neuroscience, Springer Verlag, 2007, 23 (3), pp.349-98. ⟨10.1007/s10827-007-0038-6⟩
Journal of Computational Neuroscience, 2007, 23 (3), pp.349-98. ⟨10.1007/s10827-007-0038-6⟩
ISSN: 1573-6873
0929-5313
DOI: 10.1007/s10827-007-0038-6
Popis: We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.
Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007)
Databáze: OpenAIRE
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