Skip to main content

The Effect of Different Types of Synaptic Plasticity on the Performance of Associative Memory Networks with Excitatory and Inhibitory Sub-populations

  • Conference paper
Information Processign in Cells and Tissues (IPCAT 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7223))

  • 967 Accesses

Abstract

In real neuronal networks it is known that neurons are either excitatory or inhibitory. However, it is not known whether all synapses within the subpopulations are plastic. It is interesting to investigate the implications these constraints may have on functionality. Here we investigate highly simplified models of associative memory with a variety of allowed synaptic plasticity regimes. We show that the allowed synaptic plasticity does indeed have a large effect on the performance of the network and that some regimes are much better than others.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Kullmann, D.M., Lamsa, K.P.: Long-term synaptic plasticity in hippocampal interneurons. Nat. Rev. Neurosci. 8(9), 687–699 (2007)

    Article  Google Scholar 

  2. Davey, N., Calcraft, L., Adams, R.: High capacity, small world associative memory models. Connection Science 18(3), 247–264 (2006)

    Article  Google Scholar 

  3. Braitenberg, V.: Some arguments for a theory of cell assemblies in the cerebral cortex. In: Neural Connections, Mental Computation, pp. 137–145. The MIT Press, Cambridge (1989)

    Google Scholar 

  4. Braitenberg, V., Schuz, A.: Cortex: Statistics and Geometry of Neuronal Connectivity, 2nd edn. Springer, Heidelberg (1998)

    Google Scholar 

  5. Chen, W., Maex, R., Steuber, V., Davey, N.: Clustering predicts memory performance in networks of spiking and non-spiking neurons. Frontiers in Computational Neuroscience 5, 14 (2011)

    Google Scholar 

  6. Calcraft, L.: Measuring the Performance of Associative Memories. University of Hertfordshire Technical Report, 420 (2005)

    Google Scholar 

  7. Davey, N., Adams, R.: Sign Constrained High Capacity Associative Memory Models. In: Kaynak, O., Alpaydın, E., Oja, E., Xu, L. (eds.) ICANN 2003 and ICONIP 2003. LNCS, vol. 2714, pp. 78–81. Springer, Heidelberg (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Metaxas, A., Maex, R., Steuber, V., Adams, R., Davey, N. (2012). The Effect of Different Types of Synaptic Plasticity on the Performance of Associative Memory Networks with Excitatory and Inhibitory Sub-populations. In: Lones, M.A., Smith, S.L., Teichmann, S., Naef, F., Walker, J.A., Trefzer, M.A. (eds) Information Processign in Cells and Tissues. IPCAT 2012. Lecture Notes in Computer Science, vol 7223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28792-3_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28792-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28791-6

  • Online ISBN: 978-3-642-28792-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics