Editing Neural Darwinism (section)

=== Variation in biological systems – degeneracy, complexity, robustness, and evolvability ===
[[File:06 chart pu3.png|thumb|The degeneracy of the genetic code buffers biological systems from the effects of random [[mutation]]. The ingenuous 1964 [[Nirenberg and Leder experiment]] would identify the [[mRNA]] [[codons]], a triplet sequence of [[ribonucleotides]], that coded for each [[amino acid]]; thus elucidating the [[universal genetic code]] within the [[DNA]] when the [[Transcription (biology)|transcription]] process was taken into account. Changes in the third position of the codon, the [[wobble position]], often result in the same amino acid, and oftentimes the choice comes down to [[purine]] or [[pyrimidine]] only when a choice must be made.  Similar, but variant, codon sequences tend to yield similar classes of amino acid – [[Chemical polarity|polar]] to polar, [[Chemical polarity#Nonpolar molecules|non-polar]] to non-polar, [[acidic]] to acidic, and [[Base (chemistry)|basic]] to basic residues.]]
[[File:Overview proteinogenic amino acids-ENG.svg|thumb|The four major classes of biological amino acids – polar (hydrophilic), nonpolar (hydrophobic), acidic, and basic side chain residues.  The amino acid backbone is [[amino]] group linked to an [[alpha carbon]], on which resides the side chain residue and a hydrogen atom, that is connected to a terminal [[carboxylate]] group. Aside from the disulfide bridge, there are quite a number of degenerate combinations of sidechain residues that make up the [[tertiary structure]] ([[H-bonding]], [[hydrophobic]], and [[ionic bridge]]s) in the determination of protein structure.]]
[[File:Relationships between degeneracy, complexity, robustness, and evolvability.png|thumb|left|Relationships between degeneracy, complexity, robustness, and evolvability – 1) degeneracy is the source of robustness. 2) degeneracy is positively correlated with complexity. 3) degeneracy increases evolvability. 4) evolvability is a prerequisite for complexity. 5) complexity increases to improve robustness. 6) evolvability emerges from robustness.]]

Degeneracy, and its relationship to variation, is a key concept in neural Darwinism. The more we deviate from an ideal form, the more we are tempted to describe the deviations as imperfections. Edelman, on the other hand, explicitly acknowledges the structural and dynamic variability of the nervous system. He likes to contrast the differences between redundancy in an engineered system and [[Degeneracy (biology)|degeneracy]] in a biological system. He proceeds to demonstrate how the "noise" of the computational and algorithmic approach is actually beneficial to a somatic selective system by providing a wide, and degenerate, array of potential recognition elements.{{sfn|Tononi|Sporns|Edelman|1999}}

Edelman's argument is that in an engineered system,

* a known problem is confronted
* a logical solution is devised
* an artifice is constructed to implement the resolution to the problem

To insure the robustness of the solution, critical components are replicated as exact copies. Redundancy provides a fail-safe backup in the event of catastrophic failure of an essential component but it is the same response to the same problem once the substitution has been made.

If the problem is predictable and known ahead of time, redundancy works optimally. But biological systems face an open and unpredictable arena of spacetime events of which they have no foreknowledge of. In this arena, redundancy fails - a response might be designed to the wrong problem.

Variation fuels degeneracy; degeneracy provides somatic selective systems with more than one way to solve a problem and the propensity to reuse a solution on other problems. This property of degeneracy makes the system more adaptively robust in the face of unforeseen contingencies: When one particular solution fails unexpectedly, there are other unaffected pathways that can be engaged in pursuit of the same end. Early on, Edelman spends considerable time contrasting degeneracy vs. redundancy, bottom-up vs. top-down processes, and selectionist vs. instructionist explanations of biological phenomena.