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Kalman filter control of a model of spatiotemporal cortical dynamics

Steven J Schiff1 and Tim Sauer2

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Recent advances in Kalman filtering to estimate system state and parameters in nonlinear systems have offered the potential to apply such approaches to spatiotemporal nonlinear systems. We here adapt the nonlinear method of unscented Kalman filtering to observe the state and estimate parameters in a computational spatiotemporal excitable system that serves as a model for cerebral cortex. We demonstrate the ability to track spiral wave dynamics, and to use an observer system to calculate control signals delivered through applied electrical fields. We demonstrate how this strategy can control the frequency of such a system, or quench the wave patterns, while minimizing the energy required for such results. These findings are readily testable in experimental applications, and have the potential to be applied to the treatment of human disease.


PACS

87.19.L- Neuroscience

87.18.Hf Spatiotemporal pattern formation in cellular populations

87.19.X- Diseases

87.19.R- Mechanical and electrical properties of tissues and organs

Subjects

Medical physics

Biological physics

Dates

Issue 1 (15 March 2008)

Received 10 August 2007, accepted for publication 13 November 2007

Published 10 December 2007



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