Information-selectivity of beta-amyloid pathology in an associative memory model

Frontiers in Computational Neuroscience

Volumn , Issue JANUARY 2012, 2012, Pages

  Rowan, Mark ^a  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

Alzheimer's disease; Amyloid; Associative memory; Computational model; Information; Synaptic scaling

Indexed keywords

ALZHEIMER'S DISEASE; AMYLOID; ASSOCIATIVE MEMORIES; COMPUTATIONAL MODEL; INFORMATION; SYNAPTIC SCALING;

ASSOCIATIVE PROCESSING; ASSOCIATIVE STORAGE; GLYCOPROTEINS; INFORMATION THEORY; PATHOLOGY;

DISEASES;

AMYLOID BETA PROTEIN;

ALZHEIMER DISEASE; ARTICLE; ASSOCIATIVE MEMORY; BRAIN REGION; COGNITION; COGNITIVE DEFECT; DISEASE COURSE; NERVE CELL; PREDICTION; PROBABILITY; SIMULATION; SYNAPSE;

EID: 84856799916     PISSN: 16625188     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncom.2012.00002     Document Type: Article

References (38)

1. Abbott, L. F. (1999). Lapicque's introduction of the integrate-and-fire model neuron (1907). Brain Res. Bull. 50, 303-304.
2. Abeles, M., Vaadia, E., and Bergman, H. (1990). Firing patterns of single units in the prefrontal cortex and neural network models. Network 1, 13-25.
3. Ballatore, C., Virginia, M. Y. L., and Trojanowski, J. Q. (2007). Tau-mediated neurodegeneration in Alzheimer's disease and related disorders. Nat. Rev. Neurosci. 8, 663-672.
4. Berridge, M. J. (2010). Calcium hypothesis of Alzheimer's disease. Pflugers Arch. 459,441-449.
5. Berridge, M. J., Lipp, P., and Bootman, M. D. (2000). The versatility and universality of calcium signalling. Nat. Rev. Mol. Cell Biol. 1, 11-21.
6. Borst, A., and Theunissen, F. E. (1999). Information theory and neural coding. Nat. Neurosci. 2, 947-958.
7. Bullmore, E., and Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186-198.
8. Churchland, P. S., and Sejnowski, T. J. (1994). The Computational Brain. Cambridge, MA: The MIT press.
9. Clapham, D. E. (2007). Calcium signaling. Cell 131, 1047-1058.
10. Demuro, A., Parker, I., and Stutzmann, G. E. (2010). Calcium signaling and amyloid toxicity in Alzheimer's disease. J. Biol. Chem. 285, 12463-12468.
11. Duch, W. (2007). Computational models of dementia and neurological problems. Methods Mol. Biol. 401, 305-336.
12. Gurney, K. (1997). An Introduction to Neural Networks. London: UCL Press.
13. Hardy, J. (2009). The amyloid hypothesis for Alzheimer's disease: a critical reappraisal. J. Neurochem. 110, 1129-1134.
14. Hardy, J., and Selkoe, D. J. (2002). The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics. Science 297, 353.
15. Horn, D., Levy, N., and Ruppin, E. (1996). Neuronal-based synaptic compensation: a computational study in Alzheimer's disease. Neural Comput. 8, 1227-1243.
16. Horn, D., Ruppin, E., Usher, M., and Herrmann, M. (1993). Neural network modeling of memory deterioration in Alzheimer's disease. Neural Comput. 5, 736-749.
17. Hynd, M. R., Scott, H. L., and Dodd, P. R.(2004).Glutamate-mediated excitotoxicity and neurodegeneration in Alzheimer's disease. Neurochem. Int. 45, 583-595.
18. Kopelman, M. D. (1989). Remote and autobiographical memory, temporal context memory and frontal atrophy in Korsakoff and Alzheimer patients. Neuropsychologia 27,437-460.
19. LaFerla, F. M., Green, K. N., and Oddo, S. (2007). Intracellular amyloid-β in Alzheimer's disease. Nat. Rev. Neurosci. 8, 499-509.
20. Linsker, R. (1988). Self-organization in a perceptual network. Computer 21, 105-117.
21. Minati, L., Edginton, T., Grazia Bruzzone, M., and Giaccone, G. (2009). Reviews: current concepts in Alzheimer's disease: a multidisciplinary review. Am. J. Alzheimers Dis. Other Demen. 24, 95.
22. O'Reilly, R. C., and Rudy, J. W. (2000). Computational principles of learning in the neocortex and hippocampus. Hippocampus 10, 389-397.
23. Paninski, L. (2003). Estimation of entropy and mutual information. Neural Comput. 15, 1191-1253.
24. Panzeri, S., and Treves, A. (1996). Analytical estimates of limited sampling biases in different information measures. Network 7, 87-108.
25. Rolls,E.T. (2010).A computational theory of episodic memory formation in the hippocampus. Behav. Brain Res. 215, 180-196.
26. Rolls, E. T., and Kesner, R. P. (2006). A computational theory of hippocampal function, and empirical tests of the theory. Prog. Neurobiol. 79, 1-48.
27. Rolls, E. T., Treves, A., and Tovee, M. J. The representational capacity of the distributed encoding of information provided by populations of neurons in primate temporal visual cortex. Exp. Brain Res. 114, 149-162.
28. Rowan, M. (2011). "Effects of compensation, connectivity and tau in a computational model of Alzheimer's disease," in Proceeding of the 2011 International Joint Conference on Neural Networks (IJCNN) (IEEE), San Jose, CA, 543-550.
29. Ruppin, E., and Reggia, J. A. (1995a). A neural model of memory impairment in diffuse cerebral atrophy. Br. J. Psychiatry 166, 19-28.
30. Ruppin, E., and Reggia, J. A. (1995b). Patterns of functional damage in neural network models of associative memory. Neural Comput. 7, 1105-1127.
31. Savioz, A., Leuba, G., Vallet, P. G., and Walzer, C. (2009). Contribution of neural networks to Alzheimer disease's progression. Brain Res. Bull. 80,309-314.
32. Skaggs, W. E., McNaughton, B. L., Gothard, K. M., and Markus, E. J. (1993). "An information- theoretic approach to deciphering the hippocampal code," in Proceedings of the Advances in Neural Information Processing Systems 5, NIPS Conference (San Francisco, CA: Morgan Kaufmann Publishers Inc.), 1030-1037.
33. Small, H. (2008). Network dysfunction in Alzheimer's disease: does synaptic scaling drive disease progression? Trends Mol. Med. 14, 103-108.
34. Treves, A., and Rolls, E.T. (1991). What determines the capacity of autoassociative memories in the brain? Network 2, 371-397.
35. Tsodyks, M. V., and Feigel'Man, M. V. (1988). The enhanced storage capacity in neural networks with low activity level. Europhys. Lett. 6, 101-105.
36. Wallenstein, G. V., and Hasselmo, M. E. (1998). "Neural networks and psychopathology: Connectionist models in practice and research," in Are there Common Neural Mechanisms for Learning, Epilepsy, and Alzheimer's disease? chap. 12, eds D. J. Stein and J. Ludik, Cambridge, 316-344.
37. Watts, D. J., and Strogatz, S. H. Collective dynamics of "small-world" networks. Nature 393, 440-442.
38. Wilcock, D. M., Gharkholonarehe, N., Van Nostrand, W. E., Davis, J., Vitek, M. P., and Colton, C. A. (2009). Amyloid reduction by amyloid-β vaccination also reduces mouse tau pathology and protects from neuron loss in two mouse models of Alzheimer's disease. J. Neurosc. 29, 7957.