Abstract
Cell assemblies in neural network are often assumed as overlapping, i.e. a neuron may belong to several of them simultaneously. We argue that network structures with overlapping cell assemblies can exhibit faster learning comparing to non-overlapping ones. In such structures newly trained assemblies take advantage of their overlaps with the already trained neighbors. The assemblies learned in such manner nevertheless preserve the ability for subsequent separate firing. We discuss the implications it may have for intensification of neural network training methods and we also propose to view this learning speed-up in a broader context of inter-assembly cooperation useful for modeling concept formation in human thinking.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Hebb, D.O.: The Organization of Behavior. A Neuropsychological Theory. John Wiley, New York (1949)
Palm, G.: Neural Assemblies. Studies of Brain Function, vol. VII. Springer, Heidelberg (1982)
Wickelgren, W.A.: Webs, Cell Assemblies, and Chunking in Neural Nets. Canadian Journal of Experimental psychology 53(1), 118–131 (1999)
Strangman, G.: Detecting Synchronous Cell Assemblies with Limited Data and Overlapping Assemblies. Neural Computation 9, 51–76 (1997)
Huyk, C.R.: Overlapping Cell Assemblies from Correlators. Neurocomputing 56, 435–439 (2004)
Hopfield, J.: Neural Nets and Physical Systems with Emergent Collective Computational Abilities. Proc. of the Nat. Academy of Sciences USA 79, 2554–2558 (1982)
Amit, D.J., Brunel, N.: Learning Internal Representations in an Attractor Neural Network. Network 6, 359–388 (1995)
Brunel, N.: Hebbian Learning of Context in Recurrent Neural Networks. Neural Computation 8, 1677–1710 (1996)
Kursin, A.: Neural Network: Input Anticipation May Lead To Advanced Adaptation Properties. In: Kaynak, O. (ed.) Artificial Neural Networks and Neural Information Processing, pp. 779–785. Springer, Heidelberg (2003)
Kursin, A.: Self-Organization of Anticipatory Neural Network. Scientific Proceedings Of Riga Technical University, Riga. series Computer Science, Information Technology and Management Science, pp. 51–59 (2004)
Lakoff, G., Johnson, M.: Metaphors We Live By. Univ. of Chicago Press, Chicago (1980)
Huyck, C., Orengo, V.: Information Retrieval and Categorisation using a Cell Assembly Network. Neural Computing & Applications 14(4), 282–289 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kursin, A., Húsek, D., Neruda, R. (2006). Faster Learning with Overlapping Neural Assemblies. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_24
Download citation
DOI: https://doi.org/10.1007/11840817_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38625-4
Online ISBN: 978-3-540-38627-8
eBook Packages: Computer ScienceComputer Science (R0)