Abstract
Memories can be maintained for very long periods of time, even during our whole lifetime. A fundamental dogma in the Neurosciences is that memories are engraved in the brain via specific, long-term, alterations in synaptic efficacies. However, synaptic turnover is relatively widespread in the mature nervous system1,2,3. How then are memories maintained for very long periods? Clearly memories can be maintained if synaptic weights can be kept fixed, which is the purpose of several mechanisms that were suggested in the literature. An interesting alternative, that we will explore below, is maintaining memories with altered synaptic values, i.e., synapses change dynamically and still encode the original memories4.
Keywords
Random Input Synaptic Efficacy Neuronal Regulatory Memory Pattern Neural Network DevelopmentPreview
Unable to display preview. Download preview PDF.
References
- 1.P. Goelet, V.F. Castellucci, S. Schacher, and E.R. Kandel. The long and the short of long-term memory-a molecular framwork. Nature, 322: 419–422, (1986).PubMedCrossRefGoogle Scholar
- 2.J. Lisman. The CAM kinase hypothesis for the storage of synaptic memory. Trends In Neural Science, 17(10): 406–412, (1994).CrossRefGoogle Scholar
- 3.J. R. Wolff, R. Laskawi, W.B. Spatz, and M. Missler. Structural dynamics of synapses and synaptic components. Behavioural Brain Research, 66: 13–20, (1995).PubMedCrossRefGoogle Scholar
- 4.J. L. Kavanau. Sleep and dynamic stabilization of neural circuitry: a review and synthesis. Behavioural Brain Research, 63: 111–126, (1994).PubMedCrossRefGoogle Scholar
- 5.D. Horn, N. Levy, and E. Ruppin. Memory maintenance via neuronal regulation. Neural Computation, 10(1), (1998).Google Scholar
- 6.A. van Ooyen. Activity-dependent neural network development. Network, 5: 401–423, 1994.CrossRefGoogle Scholar
- 7.G. G. Turrigiano, K. Leslie, N. Desai, and S.B. Nelson. A biological mechanism for synaptic stability in developing neocortical circuits, these proceedings.Google Scholar
- 8.M. V. Tsodyks. Associative memory in neural networks with the hebbian learning rule. Modern Physics Letters B, 3(7): 555–560, (1989).CrossRefGoogle Scholar
- 9.F. Crick, and G. Mitchison. The function of dream sleep. Nature 304, 111–114 (1983).PubMedCrossRefGoogle Scholar
- 10.J. J. Hopfield, D.I. Feldman, and R.G. Palmer. ‘Unlearning’ has a stabilizing effect in collective memories. Nature 304, 158–159 (1983).PubMedCrossRefGoogle Scholar
- 11.J. A. Hobson, and R.W. McCarley. The brain as a dream state generator: an activation-synthesis hypothesis of the dream process. Am. Jour, of Psychiatry 134, 1335–1368 (1977).Google Scholar
- 12.C. Bertoni-Freddari, W. Meier-Ruge, and J. Ulrich. Quantitative morphology of synaptic plasticity in the aging brain. Scanning Microsc, 2, 1027–1034 (1988).PubMedGoogle Scholar
- 13.C. Bertoni-Freddari, P. Fattoretti, T. Casoli, W. Meier-Ruge, and J. Ulrich. Morphological adaptive response of the synaptic junctional zones in the human dentate gyms during aging and Alzheimer’s disease. Brain Research, 517, 69–75 (1990).PubMedCrossRefGoogle Scholar
- 14.D. Horn, N. Levy, and E. Ruppin. Neuronal-Based Synaptic Compensation: A Computational Study in Alzheimer’s Disease. Neural Computation, 8, 1227–1243 (1996).PubMedCrossRefGoogle Scholar
- 15.D. Horn, and E. Ruppin. Compensatory Mechanisms in Attractor Neural Network Model of Schizophrenia. Neural Computation, 7(1), 182–205 (1995).PubMedCrossRefGoogle Scholar
- 16.E. Ruppin. Neural modeling of psychiatric disorders. Network, 6, 636–656 (1995).CrossRefGoogle Scholar