Bear in mind that my argument thus far focuses on evolution and exaptation. Another question remains. Are the concepts of subassembly tool use, hierarchical tree structure of syntax (including recursion), and conceptual recursion mediated by separate modules in the brains of modern humans? How autonomous, really, are these modules in our brains? Would a patient with apraxia (the inability to mime the use of tools) caused by damage to the supramarginal gyrus also have problems with subassembly in tool use? We know that patients with Wernicke’s aphasia produce syntactically normal gibberish—the basis for suggesting that, at least in modern brains, syntax doesn’t depend on the recursive-ness of semantics or indeed of high-level embedding of concepts within concepts.3
But how syntactically normal is their gibberish? Does their speech—mediated entirely by Broca’s area on autopilot—really have the kinds of syntactic tree structure and recursion that characterize normal speech? If not, are we really justified in calling Broca’s area a “syntax box”? Can a Broca’s aphasic do algebra, given that algebra also requires recursion to some extent? In other words, does algebra piggyback on preexisting neural circuits that evolved for natural syntax? Earlier in this chapter I gave the example of a single patient with Broca’s aphasia who could do algebra, but there are precious few studies on these topics, each of which could generate a PhD thesis.
SO FAR I have taken you on an evolutionary journey that culminated in the emergence of two key human abilities: language and abstraction. But there is another feature of human uniqueness that has puzzled philosophers for centuries, namely, the link between language and sequential thinking, or reasoning in logical steps. Can we think without silent internal speech? We have already discussed language, but we need to be clear about what is meant by thinking before we try grappling with this question. Thinking involves, among other things, the ability to engage in open-ended symbol manipulation in your brain following certain rules. How closely are these rules related to those of syntax? The key phrase here is “open-ended.”
To understand this, think of a spider spinning a web and ask yourself, Does the spider have knowledge about Hooke’s law regarding the tension of stretched strings? The spider must “know” about this in some sense, otherwise the web would fall apart. Would it be more accurate to say that the spider’s brain has tacit, rather than explicit, knowledge of Hooke’s law? Although the spider behaves as though it knows this law—the very existence of the web attests to this—the spider’s brain (yes, it has one) has no explicit representation of it. It cannot use the law for any purpose other than weaving webs and, in fact, it can only weave webs according to a fixed motor sequence. This isn’t true of a human engineer who consciously deploys Hooke’s law, which she learned and understood from physics textbooks. The human’s deployment of the law is open-ended and flexible, available for an infinite number of applications. Unlike the spider he has an explicit representation of it in his mind—what we call understanding. Most of the knowledge of the world that we have falls in between these two extremes: the mindless knowledge of a spider and the abstract knowledge of the physicist.
What do we mean by “knowledge” or “understanding”? And how do billions of neurons achieve them? These are complete mysteries. Admittedly, cognitive neuroscientists are still very vague about the exact meaning of words like “understand,” “think,” and indeed the word “meaning” itself. But it is the business of science to find answers step by step through speculation and experiment. Can we approach some of these mysteries experimentally? For instance, what about the link between language and thinking? How might you experimentally explore the elusive interface between language and thought?
Common sense suggests that some of the activities regarded as thinking don’t require language. For example, I can ask you to fix a light-bulb on a ceiling and show you three wooden boxes lying on the floor. You would have the internal sense of juggling the visual images of the boxes—stacking them up in your mind’s eye to reach the bulb socket—before actually doing so. It certainly doesn’t feel like you are engaging in silent internal speech—“Let me stack box A on box B,” and so on. It feels as if we do this kind of thinking visually and not by using language. But we have to be careful with this deduction because introspection about what’s going in one’s head (stacking the three boxes) is not a reliable guide to what’s actually going on. It’s not inconceivable that what feels like the internal juggling of visual symbols actually taps into the same circuitry in the brain that mediates language, even though the task feels purely geometric or spatial. However much this seems to violate common sense, the activation of visual image–like representations may be incidental rather than causal.
Let’s leave visual imagery aside for the moment and ask the same question about the formal operations underlying logical thinking. We say, “If Joe is bigger than Sue, and if Sue is bigger than Rick, then Joe must be bigger than Rick.” You don’t have to conjure up mental images to realize that the deduction (“then Joe must be…”) follows from the two premises (“If Joe is…and if Sue is…”). It’s even easier to appreciate this if you substitute their names with abstract tokens like A, B, and C: If A > B and B > C, then it must be true that A > C. We also can intuit that if A > C and B > C, it doesn’t necessarily follow that A > B.
But where do these obvious deductions, based on the rules of transitivity, come from? Is it hardwired into your brain and present at birth? Was it learned from induction because every time in the past, when any entity A was bigger than B and B was bigger than C, it was always the case that A was bigger than C as well? Or was it learned initially through language? Whether this ability is innate or learned, does it depend on some kind of silent internal language that mirrors and partially taps into the same neural machinery used for spoken language? Does language precede propositional logic, or vice versa? Or perhaps neither is necessary for the other, even though they mutually enrich each other.
These are intriguing theoretical questions, but can we translate them into experiments and find some answers? Doing so has proved to be notoriously difficult in the past, but I’ll propose what philosophers would call a thought experiment (although, unlike philosophers’ thought experiments, this one can actually be done). Imagine I show you three boxes of three different sizes on the floor and a desirable object dangling from a high ceiling. You will instantly stack the three boxes, with the largest one at the bottom and the smallest at the top, and then climb up to retrieve the reward. A chimp can also solve this problem but presumably requires physical trial-and-error exploration of the boxes (unless you pick an Einstein among chimps).
But now I modify the experiment: I put a colored luminous spot on each of the boxes—red (on the big box), blue (intermediate box), and green (small box)—and have the boxes lying separately on the floor. I bring you into the room for the first time and expose you to the boxes long enough for you to realize which box has which spot. Then I switch the room lights off so that only the luminous colored dots are visible. Finally, I bring a luminous reward into the dark room and dangle it from the ceiling.
If you have a normal brain you will, without hesitation, put the red-dotted box at the bottom, the blue-dotted box in the middle, and the green-dotted box on top, and then climb to the top of the pile to retrieve the dangling reward. (Let’s assume the boxes have handles sticking out that you use to pick them up with, and that the boxes have been made equal weight so that you can’t use tactile cues to distinguish them.) In other words, as a human being you can create arbitrary symbols (loosely analogous to words) and then juggle them entirely in your brain, doing a virtual-reality simulation to discover a solution. You could even do this if during the first phase you were shown only the red-and green-dotted boxes, and then separately shown the green-and blue-dotted boxes, followed finally in the test phase by seeing the red-and green-dotted boxes alone. (Assume that stacking even two boxes gives you better access to the reward.) Even though the relative sizes of the boxes were not currently visible during these three viewing stages, I bet you could now juggle the symbols entirely in your head to establish the transitivity using conditional (if-then) statements—“If red is bigger than blue and blue is bigger than green, then red must be bigger than green”—and then proceed to stack the green box on the red box in the dark to reach the reward. An ape would almost certainly fail at this task, which requires off-line (out of sight) manipulation of arbitrary signs, the basis of language.