Abstract
In this paper, we investigate the effect of synaptogenesis on memories in the brain, using the abstract-associative memory model, Hopfield model with the zero-order synaptic decay. Using the numerical simulation, we demonstrate the possibility that synaptogenesis plays a role in maintaining recent memories embedded in the network while avoiding overloading. For the network consisting of 1000 units, it turned out that the minimum decay rate to avoid overloading is 0.02, and the optimal decay rate to maximize the storage capacity is 0.08. We also show that the average numbers of replacement synapses at each learning step corresponding to these two values are 1187 and 21024, respectively.
Similar content being viewed by others
References
Hopfield JJ (1982) Neural networks and physical systems with emergent collective computational abilities. Proc Natl Acad Sci 79:2554–2558
Amari S (1989) Characteristics of sparsely encoded associative memory. Neural Netw 2:451–457
Okada M (1996) Notions of associative memory and sparse coding. Neural Netw 9(8):1429–1458
Amit DJ, Gutfreund H, Sompolinsky H (1985) Storing infinite numbers of patterns in a spin-glass model of neural networks. Phys Rev Lett 55(14):1530–1533
Mezard M, Nadal JP, Toulouse G (1986) Solvable models of working memories. J Phys 47:1457–1462
Tominaga-Yoshino K, Kondo S, Tamotsu S, Ogura A (2002) Retitive activation of protein kinase A induces slow and persistent synaptogenesis in cultured hippocampus. Neurosci Res 44:357–367
Yasumatsu N, Matsuzaki M, Miyazaki T, Noguchi J, Kasai H (2008) Principles of long-term dynamics of dendritic spines. J Neurosci 28(50):13592–13608
Altman J (1962) Are new neurons formed in the brains of adult mammals? Science 135:1127–1128
Eriksson PS, Perfilieva E, Bjork-Eriksson T et al (1998) Neurogenesis in the adult human hippocampus. Nature Med 4(11):1313–1317
Date A, Kurata K (2008) A property of neural networks of associative memory models with replacing units. Artif Life Robot 12:291–294
Ishikawa M (1996) Structural learning with forgetting. Neural Netw 9(3):509–521
Hertz J, Krogh A, Palmer RG (1991) Introduction to the theory of neural computation. Addison Wesley, Canada.
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Miyata, R., Aonishi, T., Tsuzurugi, J. et al. Properties of Hopfield model with the zero-order synaptic decay. Artif Life Robotics 17, 163–167 (2012). https://doi.org/10.1007/s10015-012-0033-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10015-012-0033-5