Charles Darwin appreciated the creative power of natural
It was evident in paleontology - the fossil history of life on
Earth, and in his observations of the
divergence of contemporary living species.
Today we see natural selection in many places besides
In our immune system antibody molecules are produced by cells in our blood stream that are self-selected to proliferate, by their reaction to foreign body antigen molecules. Gerald Edelman got his Nobel prize for his work on the biochemistry of this adaptation.
In anatomic development, especially in the nervous system, cells
proliferate and then die unless
they make the connections to become functional.
Natural selection again.
Neural networks adapt by natural selection. There are about 100 billion neurons in the central nervous system, each making connection to about a thousand other neurons. After early childhood nerve cells ordinarily do not reproduce, but the interconnections, the synapses which can either stimulate or inhibit a response, are reinforced or attenuated depending on their activity. By this means clusters of nerve cells become specialized according to the inputs they receive, from sensory organs, from surrounding or distant neurons, and from positive or negative feedback from near and far in the brain. Thus they are constantly combing their connections for combinations that are significant, and reinforcing the ones that turn out to be useful.
Every neuron is a little decision-maker. The cell membrane acts like a chemical battery, maintaining a several-millivolt potential difference between inside and outside. When the neuron is stimulated, by an appropriate combination of input signals, a process occurs that allows potassium ions and sodium ions to penetrate the cell wall, which is like short-circuiting the battery. This produces an impulse of millivolts, that lasts several milliseconds, which propagates along the nerve fiber at hundreds of feet per second. Then the system recovers to repeat a few hundred times a second. Each impulse becomes part of the combination of inputs to each of the thousand other neurons that might be stimulated in association with the first.
So we, and other animals, have evolved the associative capability for pattern recognition, which becomes the basis for memory, and imagination, because related inputs can restimulate patterns from previous experience. [ * See paragraph added 28 June 08 below * ]
For millennia philosophers have been mystified by what they call the mind-brain problem.
They could theorize about the character of real things, and their
interaction, and they could
describe their inner experiences
but what kind of reality was that? Our perception of ourselves
and of our surroundings is not a
"physical thing" but it obviously
exists, so it must exist in another domain, call it "spirit."
But these separate domains obviously interact. We perceive things and we manipulate them. In fact our body is a thing and we trigger its muscles to manipulate it, and tools, and other things. We even perceive a tool as an extension of ourselves, and feel the force of the pliers on the object we are gripping, or the impact of the tennis racquet on the ball. Yet the perception is obviously different from the physical fact. How does that work?
Today we have clarified our thoughts about information and how we use it to wend our way and work our will in the world. Norbert Wiener, in his 1948 book Cybernetics: Control and Communication in the Animal and the Machine was fully aware of the broad significance of his new science to provide a vocabulary of ideas to conceptualize these aspects of real systems. The name Cybernetics is coined from a Greek word for governor or steersman.
Experience and purpose and behavior are ideas that we use to comprehend what happens.The ventilating system in this room has a very simple central nervous system. The thermostat processes one bit of information - one binary digit that signals when the temperature is above its set point. That signal trips a relay that turns on a cooling system and then turns it off when the room temperature is below the set point and the signal disappears. We understand the working of that system as a process - the rudimentary experience of the thermostat results in behavior of the system to regulate room temperature by using an external source of energy. That system was created with a purpose - by its Intelligent Designer - it's self-motivated to keep the room comfortable. What was mystery to Plato and Aristotle, and Descartes, and Kant, and Whitehead is now, more and more, empirical fact. What was speculation to William James and Donald Hebb has become neuroanatomy and physiology. The same functionality that facilitates the habitual repetition of familiar actions without conscious thought, the practice makes perfect of athletic performance, and which was studied in Pavlov's conditioned reflex experiments, is now being exposed in all its details.
Each associative neuron is constantly combing its inputs for a
combination that it recognizes, and
it says "Aha!" by sending a signal to the multiple neurons that connect
to its output. They receive this input and many others, and
generate signals to other neurons. And some of them
say "Aha - I recognize that combination of edges and surfaces - it
might be a table." And that
output triggers other neurons that say "If it is, then it must have
characteristics." And other
neurons that say "If so, it is. If not, it must be something
else." Of course all this is non-verbal processing and we use
word analogies to describe it.
This roundabout way of discovering reality works so well because each
associative neuron is self-motivated, checking its fan-in of inputs and
its fan-out of outputs, working in parallel with billions of
when a combination of stimulative and inhibitory signals causes a
useful output that combination is reinforced, and can be more
easily recalled. Thus we build up a memory of past experiences
that feed back into our recognition of present sensory inputs in what
calls a re-entrant system. The associative character of
information storage and retrieval is natural for a parallel -
system of neurons that are each doing their thing, and so much is
happening that we can only be aware of the naturally selected,
Let's realize that our perception is a fantastic process of pattern recognition - fantastic because we can indulge the fantasy of what might be, related to what we perceive. We automatically fill in the blanks in our visual field, the blind spot where the optic nerve exits the eye and where blood vessels cross over the retina. (The retina of the eye is anatomically inside out! The light-sensitive cells are on the outside and the connecting nerves and blood vessels are inside toward the lens!) We use our knowledge from past experience of familiar objects to recognize the whole object, not just the part that is visible from a particular viewpoint, and we correct the image automatically for the motion of our eyes. We see in our mind what's there, and what it's doing, not just the fragmentary optical image in our eyes at any moment.So all we know of an experience is the thoughts it stimulates. Therefore recalling the thoughts recalls the experience. But the thoughts are information and the experience is its display in our mind - rerunning the associations that give access to their whole context. As Edelman suggested, our experience of reality is our imagined present. We are modeling our surroundings in our brain.
A ship model is a miniature construction that communicates a reality
that is too big to fit on the shelf. A
model is an idealized
wearer of the product. A model of behavior is an example
that embodies an ideal.
And in science we recognize that our ideas about real things and
processes are idealized
representations - they are models of reality. But that's another
Another example of modeling will
clarify our thoughts about reality,
and the reality of our
Architects don't do architectural drawing any more, except for casual sketches to develop their ideas. They use computer programs that compile lists of data about their creation - locations of points and lines and surfaces in the construction. That input is facilitated by a user interface - a part of the program that displays on the screen an image of what the data represents. When the job is done the computer uses the data-list model to drive a plotter to create working drawings to represent the project, another kind of model, with dimensions and specifications for construction. And perspective drawings with shading and rendering of surfaces and surroundings to visualize the completed project.
A related application is called virtual
reality - a program that
accesses the data about a
and creates an image on the
screen of what it looks like from any
or out. We can walk
through the building and see it as it will be when finished.
An even more impressive example of virtual reality is used in flight
simulators and video games. The user wears goggles with binocular
images, which are rigged to signal the computer about the
user's head position. The resulting images change automatically as the
user looks around at the
virtual reality represented by the computer model.
The result is a very realistic experience of "being there."
But the map is not the territory, as the General Semantics people
us. It's a model that
about the territory, incorporated in a physical form of paper and
ink. Or in the GPS system you might have in your car, that
calculates your location from satellite signals and refers to map data
to create an image of the
roads you might take from where you are to
where you want to go.
So we see that this visual modeling process has three components - data to represent the reality, an implementation to view the data, and a user to react to what he sees. In our mind the data is sensory signals and the associative recall of relevant experiences, the implementation is the selective presentation to our conscious awareness of the sensory inputs in the context of our knowledge about their relevance. The user is our stream-of-consciousness awareness function which automatically selects associative pattern-recognition results that are relevant to our needs. We have evolved this selective attention function because so much goes on in our mind that we can only deal with a few refined results.
The modeling function in our mind serves a very powerful purpose - Extrapolation!
From sensory inputs and past experience we can imagine what's coming.
We know where to go to catch that fly ball
when it comes down. How do we know?
The associative connections in our
massively-parallel-processing system call
back aspects of past experiences and fit them together into our ongoing
imagination of what-to-expect. We know that that fly ball will
continue on its trajectory unless something gets in its way. And
that experience is dynamic because
it is constantly updated by new sensory input as
we zero in on our effective motions to catch the ball.
We automatically forget what was wrong in our perception of reality
and replace it with the latest
information. We, and other life forms, have evolved
the scientific method!
For its survival value! We theorize
(imagine) what to expect, compare with empirical data, and correct the
theory so that it better
models reality. A bat in
the dark, flying by sonar, or the common fly, with very different
optics, can approach and land wherever they want to, using similar but
versions of awareness of their surroundings.