[From Bill Powers (2004.10.31.0712 MST)]
Bruce Gregory (2004.1030.2253)
Anything
that you name, and which does not refer to one particular
present-time perception. “An edge” is the name of a category. A
neural
signal representing the edge of an area where the color abruptly
changes is a sensation perception.
So a category is not a perceptual signal. Once again I learn
how little
I understand PCT.
A category is indicated by a neural signal. Perhaps the thesis that isn’t
getting across is that all perceptions, everything at every level that
you experience, think, feel, and so on, is a neural signal. You may not
believe that, but that idea is what the theory is founded on.
Exactly how does a neural
signal “represent”
something? I thought neural signals were identical except in
frequency.
They are, at least to a first approximation. I suggest that you get an
introductory text on analog computing. In an analog computer, everything
is represented by identical voltages. The meaning of a voltage is
determined by the computing functions that precede and follow it. For
example, if a voltage stands for the magnitude of a force, feeding that
voltage into an integrator produces another voltage whose magnitude
stands for velocity. Connecting that voltage to the input of yet another
integrator produces a third voltage, this one standing for position. All
these voltages are physically identical; they carry no special coding to
identify what they stand for. Their meaning lies in the way they are
created and the way they relate to each other. And they prove to relate
to each other in this example just as force, velocity, and position are
really relatedin the physical world (which of course is a physical model
which exists in the form of neural signals in some brains).
If you look at any of the simulations of behavior that have been produced
by various people in the CSG or elsewhere, you’ll see that all variables
are represented the same way: as numbers, pure magnitudes. There are no
different kinds of numbers to represent different qualities or
quantities. All the meaning and significance of the numbers come from the
processes by which they are generated and the further computations to
which they are inputs.
A neural signal, or a voltage, or a fluid pressure, or a number,
“represents” something in the sense that its magnitude covaries
with the magnitude of the variable being represented. The only thing that
counts about the representation is its magnitude. A single magnitude can
represent only a single dimension of variation; thus PCT is organized
around many one-dimensional control systems rather than fewer
multidimensional control systems. The magnitude of a pressure signal
represents pressure because it covaries with the magnitude of the
pressure being sensed. The same physical signal could represent the
degree of sweetness being tasted if it came from a taste receptor and
covaried with the concentration of the relevant molecules.
When we look at the brain with instruments, we see only neural signals.
We don’t see the computations to which they are inputs and of which they
are outputs. So the signals don’t look anything like what the occupant of
that brain experiences. Yet what else could we expect? Would we expect to
see a little copy of the world running in the brain, with a little sky
and little cities and little people running around in them, one of them
being you? Would we expect to see the taste of chocolate lying there like
a lovely brown candy bar? Would we expect to see the same thing that the
brain itself represents within itself and controls when it observes what
is not in itself?
The critical organizing aspects of the brain are not in the signals but
in the computations that connect them. The idea of understanding the
brain just by tracing where signals come from and where they go is
ludicrous, yet that is the basic idea behind many theories of brain
function.
Your experiences are of the signals, but since you as a conscious entity
experience many thousands, thousands of thousands, of signals at the same
time, you also experience the interplay among them. But you do not
experience the computations – how one signal is derived from
other signals. Somehow the hidden computations give rise to the world we
experience, the one that seems to be outside us and independent of us.
That “somehow” has barely been touched, because it hasn’t even
been recognized as the main problem (except by a very few
people).
I do not pretend to understand how this picture of the insides of a brain
can be reconciled with the picture we conscious occupants of brains
experience. There are many points of correspondence between model and
experience, yet the picture is not yet clear. I am content to continue to
work on the correspondences, each new one leading to a somewhat better
understanding. What I know about tracking now seems to work both from
inside and from outside. That is a lot more than I knew 50 years ago. I
am learning things about multidimensional perception and control that I
never knew before, and that maybe nobody ever knew before. I think I am
on a good path, though I will never know where it leads.
I repeat: learn about analog computing. I got a conception of how brains
work from it that has only become more convincing as time has passed.
Maybe you will see the same things there that I saw. You won’t know
unless you try.
Best,
Bill Powers