Ever since Randy Gallistel came to UMD to give a series of
lectures that eventually became his book (with Adam King) Memory and the Computational Brain Bill Idsardi and I have been
discussing his deliberately provocative thesis that current neuroscience has
fundamentally misidentified basic brain architecture. The book argues that the
current conception of the brain in which learning is understood as rewiring of
a plastic brain via changes of synaptic conductance (what fires together wires
together) cannot be correct (connectionism
is an expression of this neuronal worldview). The argument is elaborate and I
will leave a more detailed discussion of its main argument for another post.
However, what I want to very briefly mention here is a Gallistel and King
(G&K) conjecture and some recent work that appears to relate to it. I say “appears” because, believe me, I am no
expert (in fact I am not even knowledgeable enough to be a novice) and so
readers should take what follows as essentially an impressionistic riff based
on chapter 16 of G&K’s book and a recent broadcast on Science Friday; What Your Genes Can Tell You About YourMemory. So with this caveat lector
firmly before you, my conscience is clear and my riff begins.
What is G&K’s conjecture? They argue in the book that brains must have
the architecture of classical computers. Concretely this means that brains must
be able to put things in memory, retrieve things from memory and compute over
those things stored in memory. As
computation requires applying functions to arguments, we need a way of coding
variables and operations that bind and value them. These are all operations characteristic of a
classical machine with a Turing-von Neumann (TvN) architecture. As most of cognition consists of operations
that redeem symbols from memory, computations over these symbols and subsequent
storage, the brain, the organ that secretes cognition, must have a TvN architecture. This is the conclusion. The argument is
detailed, very pedagogical and a must read.
G&K contrast the TvM conception with the currently common
view of brains. In this view, brains do not
have a TvM structure but are more like neural nets, which, G&K argue is an
inadequate physical basis for cognitive computations and so must be wrong. This
is very much a minority view. Why? Because brains don’t “look like” computers
and they do look like neural nets. Ok, it’s probably more complicated than that,
but certainly part of it as anyone who has had the misfortune to hear a
connectionist talk knows. So if G&K are right that the common view is wrong
and the brain has TvM structure then how does the brain do this? The G&K
conjecture is that the requisite structure already exists within neurons, in
its molecular structure (169):
…the genome contains complex data
structures, just as does the memory of a computer, and they are encoded in both
cases through the use of the same architecture employed in the same way: an
addressable memory in which many of the memories addressed themselves generate
probes for addresses. [There is a] close parallel between the functional
structure of computer memory and the functional structure of the molecular
machinery that carries inherited information forward in time for use in the
construction and maintenance of organic structure…
Their conjecture is that the physical platform for the kinds
of computational mechanisms we need to understand cognition exploits this same molecular
structure. DNA, RNA and proteins constitute
(part of) the cognitive code in addition tos being the chemical realization of
the genetic code.
G&K are very careful to moot this suggestion with all the
caution that it deserves. In fact to call it a ‘suggestion’ is already too
grandiose, let’s say a hunch or a guess.
This is where the Science Friday segment comes in. It appears that research
is discovering that memories are in fact molecularly coded. There are epigenetic mechanisms that code
specific memories in various brain regions by laying down the proteins of the
right kind using basically the same DNA mechanisms that code for genetic
inheritance and development. Combined
with the G&K conjecture, this discovery might be the tip of a pretty
exciting cognitive-neuroscience iceberg and has the potential of overturning a
good deal of conventional wisdom, as the scientists interviewed hint at.
This has serious implications for linguists, if true (and
recall this is all an impressionistic riff). There exists a very bad argument
that the representations that linguists know and love cannot be
“psychologically real” because they are not implementable in brain
architecture, i.e. neural nets. In my
view, this has always been a weak argument, but one that seems to have quite a
bit of suasive power to non-generative grammarians. If the G&K conjecture is on the right
track, however, there is no reason to think that brains cannot code for the
kinds of representations we regularly use to account for grammatical
competence. The question will shift from
whether they do to how they do.
Let’s end with a little parable based on some G&K remarks
(p.281). They make an interesting observation about the history of modern
biochemistry and consider its implications for current neuroscience. Watson and
Crick’s (W&C) great accomplishment was to find a way to chemically
incarnate the classical gene. Until they did their work, the gene was
considered a nice computing device, but many biologists believed that it was
not “biologically real.” W&C proved
otherwise and this entirely changed biochemistry. The field after W&C was
entirely different from the field before W&C. But what of classical genetics, how much did
it change? In contrast to biochemistry, the basics remained essentially as they
were before W&C. Biochemistry had to
“catch up” to genetics, not the other way around. This story has a moral: substitute neuroscience
for biochemistry and cognition/linguistics for genetics. There is no reason a priori to think that “hard” (and expensive) neuroscience occupies
the intellectual high ground to which “soft” (and cheap) cognition/linguistics
must accommodate itself. Matters might well be the reverse, as they were once
before when “hard” biochemistry ended up conforming to “soft” genetics. The discoveries discussed on Science Friday
make the G&K conjecture a little less farfetched and tentatively suggests
that the analogy with biochemistry/genetics is prophetic. We may be getting
ready to say bye-bye to all those inane connectionist models. Yeah!!!
