The iterated Data Rate Theorem for unstable biological dynamics
- Published
- Accepted
- Subject Areas
- Mathematical Biology, Epidemiology, Computational Science
- Keywords
- aging, chronic disease, information bottleneck, Rate Distortion Theorem, regulatory failure
- Copyright
- © 2015 Wallace
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. The iterated Data Rate Theorem for unstable biological dynamics. PeerJ PrePrints 3:e1207v1 https://doi.org/10.7287/peerj.preprints.1207v1
Abstract
Counterintuitively, unstable control systems can allow extremely rapid responses that may be strongly selected by evolutionary process. Application of an information bottleneck iteration to the Data Rate Theorem -- taking the minimum necessary rate of control information as a distortion measure -- leads to a diffusion dynamic for onset of sudden failure in such systems via the necessary convexity of the Rate Distortion Function. Imposition of maintenance mechanisms seems a necessary consequence, but those too are subject to deterioration by aging or pathological exposures. In sum, a fairly simple control theory model that iterates the Data Rate Theorem provides deep insight across a wide sweep of diseases and the chronic dysfunctions of senescence.
Author Comment
The convexity of the Rate Distortion Theorem, taking the Data Rate Theorem's minimum necessary rate of control information, provides a tool for understanding how instability can be selected by evolutionary process.