In article <862648806.30339 at dejanews.com>, e904952p at hjc.edu.sg wrote:
> I am a high school student seeking some answers.(Somehow I always seem to
> start my article by saying that)
> Recently I've thinking how can that enormous amount of information all be
> stored in one single embryo. Information describing a fully grown
> organism! In a sense a complete blueprint is in that embryo. How does this
BIG question...it'll take a little while to explain it. Got a lifetime to
spend on it? :-)
> I am studying chaos theory and I just learned that very simple dynamic
> system can generate extremely complicated behavior. An example is the
> famous Madelbrot set.(well it's not exactly a dynamic system but the
> message is the same)
> Could it be that what is stored in the embryo is a simple mapping, some
> instructions telling the embryo how to evolve. All the details such as the
> complex network of brain cells simple come about as the embryo blindly
> follows the instruction?
> Of course external feedback also plays an important role.
I'm not sure what you mean by a simple mapping...there's nothing simple
about it, and if by "mapping" you mean a one-to-one correspondence between
a chunk of code and a structure, no, I don't think so. There is no tidy
block of code that is dedicated to instructing neuron X to differentiate
a particular transmitter, and to grow an axon that extends 10 microns and
then turns left. Rather, cells are programmed with a set of properties and
rules that indirectly specify a course of development. A cell may express
a receptor that activates a large set of genes if a ligand is bound, another
set if it is not bound. Whichever set that is activated modifies the ability
of the cell to respond to other signals in the environment, which then
modify the ability of the cell to respond to more signals, and so on.
The complexity of the nervous system is an emergent property of a progressive
and self-referential modulation of gene activity during development. In
that sense, it is a lot like the complex dynamic systems modeled on computers.
Paul Z. Myers