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Proceedings Paper

Computational study on cortical spreading depression based on a generalized cellular automaton model
Author(s): Shangbin Chen; Lele Hu; Bing Li; Changcheng Xu; Qian Liu
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Paper Abstract

Cortical spreading depression (CSD) is an important neurophysiological phenomenon correlating with some neural disorders, such as migraine, cerebral ischemia and epilepsy. By now, we are still not clear about the mechanisms of CSD's initiation and propagation, also the relevance between CSD and those neural diseases. Nevertheless, characterization of CSD, especially the spatiotemporal evolution, will promote the understanding of the CSD's nature and mechanisms. Besides the previous experimental work on charactering the spatiotemporal evolution of CSD in rats by optical intrinsic signal imaging, a computational study based on a generalized cellular automaton (CA) model was proposed here. In the model, we exploited a generalized neighborhood connection rule: a central CA cell is related with a group of surrounding CA cells with different weight coefficients. By selecting special parameters, the generalized CA model could be transformed to the traditional CA models with von Neumann, Moore and hexagon neighborhood connection means. Hence, the new model covered several properties of CSD simulated in traditional CA models: 1) expanding from the origin site like a circular wave; 2) annihilation of two waves traveling in opposite directions after colliding; 3) wavefront of CSD breaking and recovering when and after encountering an obstacle. By setting different refractory period in the different CA lattice field, different connection coefficient in different direction within the defined neighborhood, inhomogeneous propagation of CSD was simulated with high fidelity. The computational results were analogous to the reported time-varying CSD waves by optical imaging. So, the generalized CA model would be useful to study CSD because of its intuitive appeal and computational efficiency.

Paper Details

Date Published: 20 February 2009
PDF: 9 pages
Proc. SPIE 7186, Optical Diagnostics and Sensing IX, 71860H (20 February 2009); doi: 10.1117/12.811305
Show Author Affiliations
Shangbin Chen, Huazhong Univ. of Science and Technology (China)
Lele Hu, Huazhong Univ. of Science and Technology (China)
Bing Li, Huazhong Univ. of Science and Technology (China)
Changcheng Xu, Huazhong Univ. of Science and Technology (China)
Qian Liu, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7186:
Optical Diagnostics and Sensing IX
Gerard L. Coté, Editor(s)

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