Editing Neural Darwinism (section)

=== Rejection of computational models, codes, and point-to-point wiring ===

Edelman was well aware of the earlier debate in immunology between the instructionists, who believed the lymphocytes of the immune system learned or was instructed about the antigen and then devised a response; and the selectionists, who believed that the lymphocytes already contained the response to the antigen within the existing population that was differentially amplified within the population upon contact with the antigen. And, he was well aware that the selectionist had the evidence on their side.

Edelman's theoretical approach in ''Neural Darwinism'' was conceived of in opposition to top-down algorithmic, computational, and instructionist approaches to explaining neural function. Edelman seeks to turn the problems of that paradigm to advantage instead; thereby highlighting the difference between bottom-up processes like we see in biology vis a vis top-down processes like we see in [[engineering]] algorithms. He sees [[neurons]] as living organisms working in cooperative and competitive ways within their local [[ecology]] and rejects models that see the brain in terms of [[computer chip]]s or [[logic gate]]s in an algorithmically organized [[machine]].

Edelman's commitment to the Darwinian underpinnings of biology, his emerging understanding of the evolutionary relationships between the two molecules he had worked with, and his background in immunology lead him to become increasingly critical and dissatisfied with attempts to describe the operation of the nervous system and brain in computational or algorithmic terms.

Edelman explicitly rejects computational approaches to explaining biology as non-biological. Edelman acknowledges that there is a conservation of phylogenetic organization and structure within the vertebrate nervous system, but also points out that locally natural diversity, variation and degeneracy abound. This variation within the nervous system is disruptive for theories based upon strict point-to-point connectivity, computation, or logical circuits based upon codes.  Attempts to understand this ''noise'' present difficulties for top-down algorithmic approaches – and, deny the fundamental facts of the ''biological'' nature of the problem.

Edelman perceived that the problematic and annoying noise of the computational circuit-logic paradigm could be reinterpreted from a population biology perspective – where that variation in the [[signal]] or architecture was actually the engine of ingenuity and robustness from a selectionist perspective.