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The evolution of an illness is one of the clues that a bedside physician uses to arrive at a diagnosis and treatment strategy for diseases that affect the nervous system. Is the onset acute or subacute? Is the clinical course self-limited, relapsing-remitting, cyclic, and chronic progressive? The impetus for studying disease dynamics comes from the mathematics and physics communities: their long experience has shown that insights into mechanism often derive from examining how dynamics change. Consequently, the time evolution of a disease is modeled as differential equations, and disease processes are described in terms of the origin, stability, and bifurcations of the model’s dynamical behaviors. In 1977, Michael Mackey and Leon Glass associated changes in physiological dynamics from healthy to unhealthy with changes in underlying control parameters (Mackey and Glass 1977). Subsequently, this concept of a dynamical...
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Mackey MC, Glass L (1977) Oscillation and chaos in physiological control systems. Science 197:287–289
Pakdaman K, Grotta-Ragazzo C, Malta CP (1998) Transient regime dynamics in continuous-time neural networks with delays. Phys Rev E 58:3623–3627
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Milton, J. (2015). Dynamics of Disease States: Overview. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6675-8_781
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DOI: https://doi.org/10.1007/978-1-4614-6675-8_781
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6674-1
Online ISBN: 978-1-4614-6675-8
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