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Design for an aging brain.

David S Thaler1

  • 1Sackler Laboratory of Molecular Genetics and Informatics, Rockefeller University, 1230 York Ave, Box 174, New York, NY 10021-6399, USA. thalerd@mail.rockefeller.edu

Neurobiology of Aging
|January 5, 2002
PubMed
Summary
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Aging systems can become more complex or simpler, depending on their attractor type. This complexity is influenced by the ratio of disturbances to responses, which changes with age, affecting system entropy and outcomes.

Area of Science:

  • Systems Biology
  • Complexity Science
  • Aging Research

Background:

  • Existing research on aging systems presents conflicting trends: some decrease in complexity, while others increase.
  • Vaillancourt and Newell (2001) proposed attractor types (point vs. oscillating) explain these divergent aging trajectories.
  • Lipsitz and Goldberger (1992) previously suggested a general decrease in complexity with age.

Discussion:

  • This commentary utilizes W. Ross Ashby's cybernetic perspective to reconcile differing aging complexity observations.
  • A model is proposed where system complexity is measured by the ratio of disturbances (D) to responses (R).
  • Disturbances are further categorized into perceived (Dp) and unavoidable (Du), influencing system entropy and outcomes.

Key Insights:

Related Experiment Videos

  • System complexity, under Ashby's framework, is proportional to the variety of disturbances relative to the variety of responses (D/R).
  • Both the variety of perceived disturbances (Dp) and responses (R) tend to decrease with age.
  • A decreasing D/R ratio correlates with reduced system complexity, while an increasing ratio leads to greater measured entropy.

    • Outlook:

    • Understanding the interplay between perceived and unavoidable disturbances is crucial for predicting aging system behavior.
    • Further research can explore how changes in Dp and R specifically drive complexity shifts in biological and other complex systems.
    • This framework offers a unified approach to analyzing aging across diverse systems, moving beyond a single direction of complexity change.