I Am a Strange Loop

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).