A Neural Network Simulation of Spreading Depression
With the use of a biologically plausible artificial neural network in which connections are modified through Grossberg’s presynaptic learning rule, it is possible to simulate the spreading depression (SD) cortical phenomenon and analyze its behavior depending on different parameters related to neural plasticity and connectivity. The neural network that simulates a simplified cortex is formed by excitatory and inhibitory locally connected neurons. The conditions for the occurrence of SD are analyzed after an external stimulus is applied to the lattice simulating the cortex.
KeywordsArtificial Neural Networks Computer Simulation Spreading Depression Traveling Wave Neural Plasticity MatLAB
Unable to display preview. Download preview PDF.
- 1.Leão, A.A.P.: Spreading depression of activity in the cerebral cortex. J. Neurophysiol 7, 359–390 (1944)Google Scholar
- 5.Kager, H., Wadman, W.J., Somjen, G.G.: Simulated seizures and spreading depression in a neuron model incorporating interstitial space and ion concentrations. J. Neurophysiol 512, 495–512 (2000)Google Scholar
- 7.Somjen, G.G.: Mechanisms of spreading depression and hypoxic spreading depression like depolarization. Physiol. Rev. 81, 1065–1096 (2001)Google Scholar
- 9.Lipton, R.B., Bigal, M.E.: Migraine: epidemiology, impact, and risk factors for progression. Headache 45(suppl. 1), S3–S13 (2005)Google Scholar
- 13.Pelaéz, J.R., Piqueira, J.R.C.: Biological clues for up-to-date artificial neurons. In: Andina, D., Phan, D.T. (eds.) Computational Intelligence: for Engineering and Manufacturing, vol. 1, pp. 1–19. Springer, Berlin (2006)Google Scholar
- 14.Hebb, D.O.: The organization of behavior. Wiley, New York (1949)Google Scholar
- 18.Desai, N.: Homeostatic plasticity in the CNS: synaptic and intrinsic forms. Journal of Physiology 97, 391–402 (2003)Google Scholar
- 19.Pelaéz, J.R., Simóes, M.G.: A Computational Model of Synaptic Metaplasticity. In: Proceedings of the International Joint Conference of Neural Networks, vol. 1, pp. 6–11 (1999)Google Scholar