I Am a Strange Loop (9 page)

Although each of these terms puts the focus on a slightly different aspect of the elusive abstraction that concerns us, they are all, from my perspective, pretty much interchangeable. And for all of these terms, I reiterate that they have to be understood as coming in
degrees
along a sliding scale, rather than as on/off, black/white, yes/no switches.

Post Scriptum

The first draft of this chapter was written two years ago, and although it discussed meat-eating and vegetarianism, it had far less on the topic than this final version does. Some months later, while I was “fleshing it out” by summarizing the short story “Pig”, I suddenly found myself questioning the dividing line that I had carefully drawn two decades earlier and had lived with ever since (although occasionally somewhat uneasily) — namely, the line between mammals and other animals.

All at once, I started feeling distinctly uncomfortable with the idea of eating chicken and fish, even though I had done so for some twenty years, and so, catching myself by surprise, I stopped “cold turkey”. And by a remarkable coincidence, my two children independently came to similar conclusions at almost exactly the same time, so that over a period of just a couple of weeks our family’s diet was transmuted into a completely vegetarian one. I’ve returned to the same spot as I was in when I was twenty-one in Sardinia, and it’s the spot I plan to stay in.

Writing this chapter thus gave rise to a totally unexpected boomerang effect on its author — and as we shall see in later chapters, such an unpredictable bouncing-back of choices one has just made, followed by the incorporation of their repercussions into one’s self-model, serves as an excellent example of the meaning of the motto “I am a strange loop.”

CHAPTER 2

This Teetering Bulb of Dread and Dream

What Is a “Brain Structure”?

I
HAVE often been asked, when people hear that my research amounts to a quest after the hidden machinery of human thought, “Oh, so that means that you study the brain?”

One part of me wants to reply, “No, no — I think about
thinking.
I think about how concepts and words are related, what ‘thinking in French’ is, what underlies slips of the tongue and other types of errors, how one event effortlessly reminds us of another, how we recognize written letters and words, how we understand sloppily spoken, slurred, slangy speech, how we toss off untold numbers of utterly bland-seeming yet never-beforemade analogies and occasionally come up with sparklingly original ones, how each of our concepts grows in subtlety and fluidity over our lifetime, and so forth. I don’t think
in the least
about the brain — I leave the wet, messy, tangled web of the brain to the neurophysiologists.”

Another part of me, however, wants to reply, “
Of course
I think about the human brain.
By definition,
I think about the brain, since the human brain is precisely the machinery that carries out human thinking.”

This amusing contradiction has forced me to ask myself, “What do I mean, and what do other people mean, by ‘brain research’?”, and this leads naturally to the question, “What are the structures in the brain that someone could in principle study?” Most neuroscientists, if they were asked such a question, would make a list that would include (at least some of) the following items (listed roughly in order of physical size):

amino acids
neurotransmitters
DNA and RNA
synapses
dendrites
neurons
Hebbian neural assemblies
columns in the visual cortex
area 19 of the visual cortex
the entire visual cortex
the left hemisphere

Although these are all legitimate and important objects of neurological study, to me this list betrays a limited point of view. Saying that studying the brain is limited to the study of physical entities such as these would be like saying that literary criticism must focus on paper and bookbinding, ink and its chemistry, page sizes and margin widths, typefaces and paragraph lengths, and so forth. But what about the high abstractions that are the heart of literature — plot and character, style and point of view, irony and humor, allusion and metaphor, empathy and distance, and so on? Where did these crucial essences disappear in the list of topics for literary critics?

My point is simple: abstractions are central, whether in the study of literature or in the study of the brain. Accordingly, I herewith propose a list of abstractions that “researchers of the brain” should be just as concerned with:

the concept “dog”
the associative link between the concepts “dog” and “bark”
object files (as proposed by Anne Treisman)
frames (as proposed by Marvin Minsky)
memory organization packets (as proposed by Roger Schank)
long-term memory and short-term memory
episodic memory and melodic memory
analogical bridges (as proposed by my own research group)
mental spaces (as proposed by Gilles Fauconnier)
memes (as proposed by Richard Dawkins)
the ego, id, and superego (as proposed by Sigmund Freud)
the grammar of one’s native language
sense of humor
“I”

I could extend this list arbitrarily. It is merely suggestive, intended to convey my thesis that the term “brain structure” should include items of this general sort. It goes without saying that some of the above-listed theoretical notions are unlikely to have lasting validity, while others may be increasingly confirmed by various types of research. Just as the notion of “gene” as an invisible entity that enabled the passing-on of traits from parents to progeny was proposed and studied scientifically long before any physical object could be identified as an actual carrier of such traits, and just as the notion of “atoms” as the building blocks of all physical objects was proposed and studied scientifically long before individual atoms were isolated and internally probed, so any of the notions listed above might legitimately be considered as invisible structures for brain researchers to try to pinpoint physically in the human brain.

Although I’m convinced that finding the exact physical incarnation of any such structure in “the human brain” (is there only one?) would be an amazing stride forward, I nonetheless don’t see why physical mapping should constitute the be-all and end-all of neurological inquiry. Why couldn’t the establishment of various sorts of precise relationships among the above-listed kinds of entities, prior to (or after) physical identification, be just as validly considered brain research? This is how scientific research on genes and atoms went on for many decades before genes and atoms were confirmed as physical objects and their inner structure was probed.

A Simple Analogy between Heart and Brain

I wish to offer a simple but crucial analogy between the study of the brain and the study of the heart. In our day, we all take for granted that bodies and their organs are made of cells. Thus a heart is made of many billions of cells. But concentrating on a heart at that microscopic scale, though obviously important, risks missing the big picture, which is that
a heart is a pump.
Analogously,
a brain is a thinking machine,
and if we’re interested in understanding what thinking is, we don’t want to focus on the trees (or their leaves!) at the expense of the forest. The big picture will become clear only when we focus on the brain’s large-scale architecture, rather than doing ever more fine-grained analyses of its building blocks.

At some point a billion years or so ago, natural selection, in its usual random-walk fashion, bumped into cells that contracted rhythmically, and little beings possessing such cells did well for themselves because the cells’ contractions helped send useful stuff here and there inside the being itself. Thus, by accident, were pumps born, and in the abstract design space of all such proto-pumps, nature favored designs that were more efficient. The inner workings of the pulsating cells making up those pumps had been found, in essence, and the cells’ innards thus ceased being the crucial variables that were selected for. It was a brand-new game, in which rival
architectures
of hearts became the chief contenders for selection by nature, and on that new level, ever more complex patterns quickly evolved.

For this reason, heart surgeons don’t think about the details of heart cells but concentrate instead on large architectural structures in the heart, just as car buyers don’t think about the physics of protons and neutrons or the chemistry of alloys, but concentrate instead on high abstractions such as comfort, safety, fuel efficiency, maneuverability, sexiness, and so forth. And thus, to close out my heart–brain analogy, the bottom line is simply that the microscopic level may well be — or rather, almost certainly is — the wrong level in the brain on which to look, if we are seeking to explain such enormously abstract phenomena as concepts, ideas, prototypes, stereotypes, analogies, abstraction, remembering, forgetting, confusing, comparing, creativity, consciousness, sympathy, empathy, and the like.

Can Toilet Paper Think?

Simple though this analogy is, its bottom line seems sadly to sail right by many philosophers, brain researchers, psychologists, and others interested in the relationship between brain and mind. For instance, consider the case of John Searle, a philosopher who has spent much of his career heaping scorn on artificial-intelligence research and computational models of thinking, taking special delight in mocking Turing machines.

A momentary digression… Turing machines are extremely simple idealized computers whose memory consists of an infinitely long (
i.e.,
arbitrarily extensible) “tape” of so-called “cells”, each of which is just a square that either is blank or has a dot inside it. A Turing machine comes with a movable “head”, which looks at any one square at a time, and can “read” the cell (
i.e.,
tell if it has a dot or not) and “write” on it (
i.e.,
put a dot there, or erase a dot). Lastly, a Turing machine has, stored in its “head”, a fixed list of instructions telling the head under which conditions to move left one cell or right one cell, or to make a new dot or to erase an old dot. Though the basic operations of all Turing machines are supremely trivial, any computation of any sort can be carried out by an appropriate Turing machine (numbers being represented by adjacent dot-filled cells, so that “•••” flanked by blanks would represent the integer 3).

Back now to philosopher John Searle. He has gotten a lot of mileage out of the fact that a Turing machine is an abstract machine, and therefore could, in principle, be built out of any materials whatsoever. In a ploy that, in my opinion, should fool only third-graders but that unfortunately takes in great multitudes of his professional colleagues, he pokes merciless fun at the idea that
thinking
could ever be implemented in a system made of such far-fetched physical substrates as
toilet paper and pebbles
(the tape would be an infinite roll of toilet paper, and a pebble on a square of paper would act as the dot in a cell), or
Tinkertoys,
or a vast assemblage of
beer cans and ping-pong balls
bashing together.

In his vivid writings, Searle gives the appearance of tossing off these humorous images light-heartedly and spontaneously, but in fact he is carefully and premeditatedly instilling in his readers a profound prejudice, or perhaps merely profiting from a preexistent prejudice. After all, it
does
sound preposterous to propose “thinking toilet paper” (no matter how long the roll might be, and regardless of whether pebbles are thrown in for good measure), or “thinking beer cans”, “thinking Tinkertoys”, and so forth. The light-hearted, apparently spontaneous images that Searle puts up for mockery are in reality skillfully calculated to make his readers scoff at such notions without giving them further thought — and sadly, they often work.