Display options
Cite
Richert M, Nageswaran JM, Dutt N, et al. An efficient simulation environment for modeling large-scale cortical processing. Front Neuroinform. 2011;5:19doi: 10.3389/fninf.2011.00019.
Richert, M., Nageswaran, J. M., Dutt, N., & Krichmar, J. L. (2011). An efficient simulation environment for modeling large-scale cortical processing. Frontiers in neuroinformatics, 519. https://doi.org/10.3389/fninf.2011.00019
Richert, Micah, et al. "An efficient simulation environment for modeling large-scale cortical processing." Frontiers in neuroinformatics vol. 5 (2011): 19. doi: https://doi.org/10.3389/fninf.2011.00019
Richert M, Nageswaran JM, Dutt N, Krichmar JL. An efficient simulation environment for modeling large-scale cortical processing. Front Neuroinform. 2011 Sep 14;5:19. doi: 10.3389/fninf.2011.00019. eCollection 2011. PMID: 22007166; PMCID: PMC3172707.
Copy Download .nbib Format: NLM
Share it on

Front Neuroinform. 2011 Sep 14;5:19. doi: 10.3389/fninf.2011.00019. eCollection 2011.

An efficient simulation environment for modeling large-scale cortical processing.

Frontiers in neuroinformatics

Micah Richert, Jayram Moorkanikara Nageswaran, Nikil Dutt, Jeffrey L Krichmar

Affiliations

  1. Department of Cognitive Sciences, University of California Irvine, CA, USA.

PMID: 22007166 PMCID: PMC3172707 DOI: 10.3389/fninf.2011.00019

Abstract

We have developed a spiking neural network simulator, which is both easy to use and computationally efficient, for the generation of large-scale computational neuroscience models. The simulator implements current or conductance based Izhikevich neuron networks, having spike-timing dependent plasticity and short-term plasticity. It uses a standard network construction interface. The simulator allows for execution on either GPUs or CPUs. The simulator, which is written in C/C++, allows for both fine grain and coarse grain specificity of a host of parameters. We demonstrate the ease of use and computational efficiency of this model by implementing a large-scale model of cortical areas V1, V4, and area MT. The complete model, which has 138,240 neurons and approximately 30 million synapses, runs in real-time on an off-the-shelf GPU. The simulator source code, as well as the source code for the cortical model examples is publicly available.

Keywords: GPU; STDP; computational neuroscience; short-term plasticity; simulation; software; spiking neurons; visual cortex

References

  1. Sci Am. 2005 May;292(5):56-63 - PubMed
  2. Neuroscientist. 2001 Apr;7(2):123-35 - PubMed
  3. J Neurosci. 1984 Jan;4(1):309-56 - PubMed
  4. Front Neuroinform. 2009 May 27;3:16 - PubMed
  5. Science. 2003 Sep 26;301(5641):1870-4 - PubMed
  6. Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4164-7 - PubMed
  7. Cereb Cortex. 2004 Aug;14(8):933-44 - PubMed
  8. Neuroinformatics. 2010 Oct;8(3):183-96 - PubMed
  9. Front Neuroinform. 2008 Nov 18;2:5 - PubMed
  10. Nat Neurosci. 2000 Sep;3(9):919-26 - PubMed
  11. J Neurosci. 2000 Dec 1;20(23):8812-21 - PubMed
  12. Front Neurosci. 2011 Feb 23;5:9 - PubMed
  13. J Comput Neurosci. 2007 Dec;23(3):349-98 - PubMed
  14. Science. 2009 Oct 16;326(5951):379-80 - PubMed
  15. Front Comput Neurosci. 2009 Jul 30;3:9 - PubMed
  16. Front Neuroinform. 2009 Jan 27;2:11 - PubMed
  17. Science. 1958 Jan 31;127(3292):238-9 - PubMed
  18. Annu Rev Neurosci. 2005;28:357-76 - PubMed
  19. Neural Comput. 2007 Nov;19(11):2881-912 - PubMed
  20. Nature. 2009 Sep 10;461(7261):263-6 - PubMed
  21. Science. 2008 Mar 14;319(5869):1543-6 - PubMed
  22. J Neurosci. 2002 Nov 1;22(21):9475-89 - PubMed
  23. J Neurophysiol. 2004 Aug;92(2):959-76 - PubMed
  24. Neural Comput. 2006 Feb;18(2):245-82 - PubMed
  25. J Neurophysiol. 2009 Jul;102(1):15-27 - PubMed
  26. Conf Proc IEEE Eng Med Biol Soc. 2006;Suppl:6702 - PubMed
  27. Neural Netw. 2009 Jul-Aug;22(5-6):791-800 - PubMed
  28. J Neurosci. 2008 Mar 26;28(13):3310-23 - PubMed
  29. Proc Natl Acad Sci U S A. 1998 Apr 28;95(9):5323-8 - PubMed
  30. Methods Mol Biol. 2007;401:103-25 - PubMed
  31. Vision Res. 1998 Mar;38(5):743-61 - PubMed
  32. Front Neural Circuits. 2010 Nov 18;4:122 - PubMed
  33. IEEE Trans Neural Netw. 2004 Sep;15(5):1063-70 - PubMed
  34. Front Neurosci. 2009 Sep 15;3(2):192-7 - PubMed
  35. J Neurophysiol. 2005 Nov;94(5):3637-42 - PubMed
  36. Neural Comput. 1997 Aug 15;9(6):1179-209 - PubMed
  37. J Neurosci. 2005 Nov 16;25(46):10786-95 - PubMed
  38. Neural Comput. 2007 Jun;19(6):1437-67 - PubMed

Publication Types