Design for an aging brain.

Neurobiol Aging

Sackler Laboratory of Molecular Genetics and Informatics, Rockefeller University, 1230 York Ave, Box 174, New York, NY 10021-6399, USA.

Published: February 2002

Vaillancourt and Newell (Neurobiol. of Aging 2001) show that although many aging systems decrease in complexity as anticipated by Lipsitz and Goldberger (JAMA 1992), other aging systems increase in complexity. Vaillancourt and Newell explain the discrepancy by proposing that systems with a point attractor decrease in complexity with age, whereas those with an oscillating attractor increase in complexity with age. Vaillancourt and Newell are certainly correct that no one direction fits all results. Aging and death sometimes follow from a system being too simple, or, too complex. A perspective, based on the work of W. Ross Ashby (1956 and http://pespmc1.vub.ac.be/ASHBBOOK.html) is used in this commentary to consider why some systems become apparently more simple and others more complex as they age. In this Ashby-inspired view the measured complexity of a system's Responses to Disturbances is proportional to the ratio D/R, where D and R are sets containing the variety of possible disturbances and responses. The model expands on Ashby's by proposing that D consists of two components, Dp and Du. Dp consists of disturbances that are a function of the system's perception. Responses to Dp are often anticipatory and the response itself dominates the outcome. Du are disturbances that are unavoidable. Outcomes decrease or increase in measured entropy as a function of changes in (Dp + Du)/R. The variety of elements in both Dp and R decrease with age. When D/R decreases with age, the system shows less complexity. Conversely when D/R increases with Age, the results become more entropic.

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