Academic journal article Cosmos and History: The Journal of Natural and Social Philosophy

Symbolic and Cognitive Theory in Biology

Academic journal article Cosmos and History: The Journal of Natural and Social Philosophy

Symbolic and Cognitive Theory in Biology

Article excerpt


Like the computer language LISP, DNA is homoiconic. Thus, a single string can be either program or data, depending on the context. Lisp uses the quote mechanism to achieve this. In particular, LISP normally uses the following syntax;

(function parameters)

This is called a form. LISP has been nicknames "lots of irritating silly parentheses" and it is fair to say that the syntax, involving embedded parentheses to arbitrary recursive depts., is initially off-putting. I ask the reader to be patient, because I believe the payoff to be worth it.

Very simply, (+ 5 3) will result in 8 being returned by the interpreter symbolized by ">"

So this is a dialogue;

> (+ 5 3) 8

We may wish, for whatever reason, to have (+ 5 3) regarded simply as a list. In that case, we put a "front" quote in front of it '(+ 5 3).. Now look what happens; > '(+ 5 3)

(+ 5 3)

So now we have non-coding, "silent' DNA. Alternative splicing in genetics is similar to an alternative prepositional phrase attachment that has been rejected. It is only a minor stretch to think of a "front" quote as modeling this. Short et al (2008) indicate how this could be used by evolution to try different possibilities.

However, LISP is infinitely more subtle than this. It may be the case that we want part of a list evaluated, and the other part left as it is. For this we can use ', or backquote. The use of comma (,) in conjunction with backquote stipulates that everything in the form immediately following the comma is to be evaluated, and the rest is to be left as it is.

Thus, we can construct a list like (print '(the answer is, (+ 5 3)) and when we get this evaluated we see; > (print '(the answer is, (+ 5 3))

(the answer is (8))

We can get rid of the parenthesis with @ > (print '(the answer is, @(+ 5 3))

(the answer is 8)

Now we have the capacity to model how various parts of a string of nucleotides might be interpreted as program or as data. There is one farther step to take; the issue of how the same string can be now program, now data, and this can be taken on faith unless the reader wants to consult the addendum at the end of this paper.


The argument of this paper in a nutshell is the following; the pressure to consider Biology to be largely a computational science in some non-trivial way will intensify in the years immediately ahead. Coupled with this will come an accompanying impetus to reify biological process with statistical analysis as its fundamental touchstone. This has already been attempted in computational analysis of natural language and has largely failed with syntax and semantics now seen as also necessary. What biology may indeed need is an articulated account of how its symbols function, and a modeling environment in which to express this. The following paper makes a gesture in this direction, with code in the appendix, and then considers larger issues of how to consider cognition as part of nature; eventually to turn the tables and ask in what sense cognition--and perhaps computation--is a biological phenomenon.

About a generation ago, it became clear that a "computational paradox" loomed in the cognitive sciences. A similar one obtains in the biology of the early third millennium. The cognitive sciences had witnessed a spectacular series of successes in AI starting from the 1950's equaled in magnitude only by the distressing failure of the early AI systems to scale, or indeed to function in real-world environments. At this point, many of us, including the present author (2003) and Bickhard (2009) following Edelman (Rose, 2003) began to argue for the necessity of biological foundation for a putatively unified "cognitive science". This of course is consonant with the reductionsist drive in science, and led to an eschatological drive in cognitive science called "eliminative materialism". …

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