Finding useful functions- part 1

From: Bill Modlin (modlin1_at_metrocast.net)
Date: 10/25/04 

Date: Mon, 25 Oct 2004 01:05:09 -0700

Our brains have innate structure tailored by evolutionary processes
over a long period of time. This structure performs functions that
contribute to our behavior in ways that somewhere along the line
probably helped individuals to survive, or at least didn't hurt.

Many of those functions are not fully determined by genetics alone.
There is an innate framework, but details are filled in by processes
of conditioning and association, and to some degree the framework
itself is mutable if environmental conditions differ sufficiently
from those for which it evolved. There are few sharp lines between
innate and acquired neural function.

Feature discrimination in the early visual system is sometimes
called innate. Certainly it is innate that the cells grow into
layers of tissue appropriate for performing useful feature
discriminations. However, it seems the specific connections and
weights to implement particular discriminations get filled in by
adaptation to correlations in the ensemble of signals flowing from
the retina. For example, we can change the distribution of
particular detectors dramatically by raising a cat in an abnormal
visual environment. It seems cells are not so much genetically
determined to perform specific discriminations, as that they acquire
discrimination functions appropriate to the signals they encounter
in their genetically determined position in the network.

There are places where neural projections bring together signals
originating from corresponding points in the left and right eyes.
This allows merging both images to fill in details missing from one
or the other, estimating depth from discrepancies in the two images,
and so on. There is genetic direction to cause axonal projections
carrying signals from one eye to grow toward the normally expected
locations of the corresponding signal paths from the other. But
(from experiments on Xenopus frogs) if one eye is surgically rotated
before the connections are formed, so that the locations of
correlated signals are altered, we see the projections grow first
toward the normal target location, then veer off sharply to connect
with the very different cells now in position to be correlated.

Many topographic maps can be found in the brain, so that for example
neigboring sections of neural tissue are excited by stimulii from
adjacent sections of skin. One might imagine a fixed wiring scheme
under genetic control to hook up these maps, but when we surgically
swap small patches of skin the connections change to preserve the
mapping. It takes some time, but after a while we find that the
moved sensors now activate sections of the remote neural map that
correspond to their new positions.

A reasonable interpretation is that the "wiring" of neural circuitry
is only loosely determined by a genetic blueprint. Most of the
actual connections (and therefore the functions performed) are
established as a result of correlations between the activities of
potentially connected cells. Not only are the initial connections
determined by correlations, but even after a stable connection
pattern is established, the connections will change if the
correlations change.

>From the viewpoint of a single cell, it strengthens connections to
others correlated with its own activity and weakens others, much as
postulated by Hebb so many years ago. While direct observation of
such changes in individual active synapses is still difficult, we
can observe at least one related mechanism in widespread use. Cells
in a child's brain sprout huge dendritic trees and eventually make
something like 200,000 synaptic connections. By adulthood these are
trimmed back to an average of 10 to 20 thousand. The only plausible
explanation for this of which I am aware is that the surviving
connections are those that showed correlation with the activity of
the cell. Uncorrelated connections simply drop out of the picture.

Overall, the point is that the functions computed by cells in the
brain are largely determined by the correlations encountered in the
signals accessible to the cell, rather than by genetic control.

This is learning or conditioning, but it is not the kind of
feedback-driven learning that is usually intended when one speaks of
operant conditioning. This sort of learning does not depend on
consequences of the output of the function, and would occur even if
the output were not connected to anything else and could therefore
have no consequences extending beyond the cell doing the learning.

>From an evolutionary perspective, such learning mechanisms exist
because they do indeed often have useful behavioral consequences.
But the evolutionary connection is between the learning mechanisms
and ensembles of behavior, not between the individual functions
learned and specific contingencies associated with those functions.

--------

None of the above should be taken as suggesting that other sorts of
learning can be ignored. To implement AI we will require an
understanding of many facets of adaptive behavior, including the
operant conditioning or reinforcement learning that has been the
sole focus of certain vocal participants in CAP.

But I do suggest that these correlation-driven "unsupervised"
mechanisms provide a critically important underpinning for other
learning paradigms, that they are necessary parts of an explanation
of how all our behavior-generating mechanisms actually work.

<to be continued in further posts>

Bill Modlin

Relevant Pages

  • Re: Finding useful functions- part 1
    ... >> There is an innate framework, but details are filled in by ... Certainly it is innate that the cells grow into ... it seems the specific connections and ... >> established as a result of correlations between the activities ...
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  • Re: Finding useful functions- part 1
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  • Re: Finding useful functions- part 1
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