Computer Models and Analysis Tools for Neural Microcircuits

  • Thomas Natschläger
  • Henry Markram
  • Wolfgang Maass


This chapter surveys web resources regarding computer models and analysis tools for neural microcircuits. In particular it describes the features of a new website ( that facilitates the creation of computer models for cortical neural microcircuits of various sizes and levels of detail, as well as tools for evaluating the computational power of these models in a Matlab-environment.

Key words

neural microcircuits spiking neurons computer simulations real-time computing learning algorithms Matlab 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Abbott, L. F., and Nelson, S. B. (2000) Synaptic plasticity: taming the beast. Nature Neurosci. 3, 1178–1183.PubMedCrossRefGoogle Scholar
  2. Auer, P., Burgsteiner, H., and Maass, W. (2002) Reducing communication for distributed learning in neural networks. Proc. ICANN’2002. Online available as # 127 on
  3. Braitenberg, V., and Schuez, A. (1998) Cortex: Statistics and Geometry of Neuronal Connectivity, 2nd ed., Springer Verlag, Berlin.Google Scholar
  4. Douglas, R., and Martin, K. (1998) Neocortex. In: The Synaptic Organization of the Brain. G. M. Shepherd, Ed., Oxford University Press, 459–509.Google Scholar
  5. Duda, R. O., Hart, P. E., and Stork, D. G. (2001) Pattern Classification, 2nd ed., John Wiley & Sons, New York.Google Scholar
  6. Gupta, A., Wang, Y., and Markram, H. (2000) Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science 287, 273–278.PubMedCrossRefGoogle Scholar
  7. Gupta, A., Silberber, G., Toledo-Rodriguez, M, Wu, C. Z., Wang, Y., and Markram, H. (2002, in press) Organizing principles of neocortical microcircuits. Cellular and Molecular Life Sciences. Google Scholar
  8. Hertz, J., Krogh, A., and Palmer, R. G. (1991) Introduction to the Theory of Neural Computation. Addison-Wesley, Redwood City, Ca.Google Scholar
  9. Hopfield, J. J., and Brody, C. D. (2001) What is a moment? Transient synchrony as a collective mechanism for spatio-temporal integration. Proc. Natl. Acad. Sci., USA, 89(3), 1282.CrossRefGoogle Scholar
  10. Legenstein, R. A., Maass, W., and Markram, H. (2002) Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons, submitted for publication. Online available as # 140 on Google Scholar
  11. Maass, W., Natschläger, T., and Markram, H. (2002, in press) Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation. Online available as # 130 on
  12. Markram, H., Lubke, J., Frotscher, M., and Sakmann, B. (1997) Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science 275, 213–215.PubMedCrossRefGoogle Scholar
  13. Markram, H., Wang, Y., and Tsodyks, M. (1998) Differential signaling via the same axon of neocortical pyramidal neurons. Proc. Natl Acad. Sci., 95, 5323–5328.PubMedCrossRefGoogle Scholar
  14. Markram, H., Ofer, M., Natschlager, T., Maass, W. (2002, in press) Temporal integration in neocortical microcircuits. Cerebral Cortex. Google Scholar
  15. Shepherd, G. M. (1988) A basic circuit for cortical organization. In: Perspectives in Memory Research, M. Gazzaniga, Ed., MIT-Press, 93–134.Google Scholar
  16. Song, S., Miller, K., and Abbott, L. F. (2000) Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neurosci. 3, 919–926.PubMedCrossRefGoogle Scholar
  17. Svahn, E. (2001) Parallel Matlab Toolbox: User Documentation. Masters Thesis, Chalmers University of Technology, Sweden. To get a copy of the toolbox contact E. Svahn (email:, or get it via Google Scholar
  18. Thomson, A., West, D. C., Wang, Y., and Bannister, A. P. (2002, in press) Synaptic connections and small circuits involving excitatory and inhibitory neurons in layers 2 to 5 of adult rat and cat neocortex: triple intracellular recordings and biocytin-labelling in vitro. Cerebral Cortex. Google Scholar
  19. Tsodyks, M., Pawelzik, K., and Markram, H. (1998) Neural networks with dynamic synapses. Neural Computation 10, 821–835.PubMedCrossRefGoogle Scholar
  20. Vapnik, V. N. (1998) Statistical Learning Theory. John Wiley, New York.Google Scholar
  21. Zador, A. (2000) The basic unit of computation. Nature Neurosci. 3, 1167.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Thomas Natschläger
    • 1
  • Henry Markram
    • 2
  • Wolfgang Maass
    • 1
  1. 1.Institute for Theoretical Computer ScienceTechnische Universität GrazAustria
  2. 2.Brain Mind InstituteEcole Polytechnique Federale de LausanneSwitzerland

Personalised recommendations