Evolution of Complexity and Neural Topologies

Yaeger, Larry S. “Evolution of complexity and neural topologies.” In Guided self-organization: Inception , pp. 415-454. Springer, Berlin, Heidelberg, 2014.
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One of the grandest and most intriguing self-organizing systems is nature itself.
Whether couched in terms of evolutionary theory (Darwin 1859), information theory
(Avery 2003), or thermodynamics and maximum physical entropy (Jaynes 1957a,b;
Swenson 1989) natural processes have yielded a remarkable diversity of behavioral
and organizational levels of complexity ranging from microbes to man.
Though one could reasonably argue that single-celled organisms are as suited to
their ecological niches as human beings are to theirs, no one would argue that microorganisms are as complex as humans. And looking at the fossil record, it is clear
that complexity, by any metric, has increased over geological time scales (Carroll
2001), from algae to plants, from ediacarans to arthropods to insects to mammals.
Understanding the nature and sources of that complexity will yield insights into all of
biology, including ourselves.

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