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NEST: Science-driven development of neuronal network simulation software

Susanne Kunkel1, 2*, Jochen M. Eppler1, 2, Hans E. Plesser3, 4, Marc-Oliver Gewaltig5, Markus Diesmann4, 6 and Abigail Morrison1, 2, 4
  • 1 Albert-Ludwig University of Freiburg, Functional Neural Circuits Group, Germany
  • 2 Bernstein Center Freiburg, Germany
  • 3 Norwegian University of Life Sciences, Department of Mathematical Sciences and Technology, Norway
  • 4 Brain Science Institute, RIKEN, Japan
  • 5 GmbH, Honda Research Institute Europe, Germany
  • 6 RIKEN Computational Science Research Program, Brain and Neural Systems Team, Japan

NEST is a simulator for heterogeneous networks of point neurons or neurons with few compartments (e.g. stick-and-ball models) [1]. It is suited for a broad range of neuronal network modeling approaches and computer architectures: from single- or multi-threaded simulations of small and medium sized networks on standard desktop computers, to distributed simulation of large networks on computer clusters or HPC facilities such as BlueGene. Distributed simulations exhibit excellent scaling up to the order of one thousand processors, and research is ongoing to extend the scalability into the range of ten thousand processors and beyond [2,3]. NEST is developed by the NEST Initiative, an international contract-based collaboration between academic and industrial research institutes.

NEST is subject to continuous development to provide its users with cutting-edge features and respond to the demands of current questions in neuroscience. Recent features include the incorporation of new neuron models such as the MAT(2) model [4] and spike-timing and neuromodulation dependent plasticity [5,6]. To increase its user-friendliness and exploit software trends in the neuroscience community, NEST enables users to extend its functionality through dynamically linked modules and interact with the software using a Python-based user interface PyNEST in addition to the native simulation language SLI [7]. NEST also supports the MUSIC interface to communicate with other simulators [8] and provides visualization tools [9] and a topology module that facilitates concise specification of spatial structure [10]. The developers also continually improve the underlying algorithms, e.g. for the calculation of 'off-grid' spike times and the integration of non-linear neuron models such as the AdEx model [11,12,13].

Frequent releases of the NEST software provide the users with the newest technology and the developers with feedback about bugs and potential improvements. Release stability is supported by an automated test suite [14]. The NEST user community is active and growing, in part due to its use in large national and international projects, such as the Next-generation supercomputing project of MEXT and FACETS as well as at summer schools, for example, the Advanced Course in Computational Neuroscience and the Okinawa Computational Neuroscience Course. A list of neuroscientific publications that use NEST is available on the website, as is the current release of the source code (www.nest-initative.org). A convenient option for those wishing to try out NEST is the LiveCD, which enables easy, platform-independent testing of our simulation software.

Acknowledgements:
Partially supported by Next-Generation Supercomputer Project of MEXT, Japan, DIP F1.2, Helmholtz Alliance on Systems Biology, EU Grant 15879 (FACETS), BMBF Grant 01GQ0420 to BCCN Freiburg, the Research Council of Norway under grant 178892/V30 (eNeuro), the Junior Professor Advancement Program of Baden-Württemberg, and the Honda Research Institute Europe GmbH.

References

1. Gewaltig M-O & Diesmann M (2007) Scholarpedia 2(4):1430

2. Plesser HE et al. (2007) Springer-Verlag LNCS 4641, 672-681

3. Kunkel S et al. (2009) Front. Neuroinform. doi: 10.3389/conf.neuro.11.2009.08.044

4. Kobayashi R et al. (2009) Front. Comput. Neurosci. 3:9

5. Morrison A et al. (2007) Neural Comput. 19, 1437-1467

6. Potjans W et al. (2010) Implementing neuromodulated plasticity in distributed simulations. (submitted)

7. Eppler JM et al. (2009) Front. Neuroinform. 2:12

8. Djurfeldt M et al. (2010) Neuroinformatics 8(1):43-60

9. Nordlie E & Plesser H (2010) Front. Neuroinform. 3:39

Conference: Neuroinformatics 2010 , Kobe, Japan, 30 Aug - 1 Sep, 2010.

Presentation Type: Poster Presentation

Topic: Large scale modeling

Citation: Kunkel S, Eppler JM, Plesser HE, Gewaltig M, Diesmann M and Morrison A (2010). NEST: Science-driven development of neuronal network simulation software. Front. Neurosci. Conference Abstract: Neuroinformatics 2010 . doi: 10.3389/conf.fnins.2010.13.00105

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Received: 15 Jun 2010; Published Online: 15 Jun 2010.

* Correspondence: Susanne Kunkel, Albert-Ludwig University of Freiburg, Functional Neural Circuits Group, Freiburg i. Br., Germany, morrison@fz-juelich.de