How Brains Think — William Calvin on Intelligence

Three drawings of the human cortex by the father of modern neuroscience, Santiago Ramón y Cajal. Source: “Comparative study of the sensory areas of the human cortex” by Santiago Ramon y Cajal (1899). Public domain via Wikimedia Commons.

Guessing and improvisation

In How Brains Think, the neurophysiologist William Calvin says it is the “beginner’s error” to conflate purpose and complexity with intelligence. Most animals, after all, are steadfast in their pursuit of survival. And many of them exhibit incredible behaviors to achieve just that. They range from the migratory patterns of butterflies to the murmurations of starlings. Such efforts, however, while ‘purposeful’ and complex, are usually ‘built in’ and inflexible.

Perhaps we can say instead then that flexibility and creativity are signs of intelligence. Dogs and chimpanzees, for example, possess many instincts. But they are also capable of learning new tricks. We might also extend the idea of intelligence to the making of novel combinations, much in the way crows combine simple tools to get food beyond the reach of their beaks.

Maybe intelligence requires some foresight and planning. Squirrels, for instance, are masterful planners. They amass nuts for the long winter. But their planning does not require much brain-power. They rely on the hormone melatonin, which releases in greater amounts during extended nights and stimulates their readying for winter. Few animals engage in the sort of “multistage planning” that we humans do every day.

The intelligence rabbit hole goes on, of course. Terms like visual-spatial intelligence, kinesthetic intelligence, and logical intelligence are also strewn about. The point is that intelligence is a fuzzy concept. It is not something we can quantify easily. This is also why intelligent quotient tests and related indicators are poor. They do not account for creativity, planning, and cross-combinations that make us who we are.

But if you pushed Calvin for a definition, he would combine the ideas of neurobiologist Horace Barlow and psychologist Jean Piaget to say that intelligence involves “guessing well”. It is “what you use when you don’t know what to do.” It reflects the animal’s capacity for novelty finding when the situation is unclear. To Calvin, intelligence is more akin to jazz improvisation than a scripted concerto.

Selecting for versatility

Definitional problems aside, flexible improvisers are rare. “Nature is full of specialists that do one thing very well”, Calvin reminds. Most living things are typecast actors in an ecological play. So why might Mother nature select for the so-called intelligence we speak of? Under what conditions might versatile animals with broad repertoires come about?

A “fickle environment”, Calvin notes, is a good place to start. Omnivores, for example, like octopuses and crows, have a wide range of behaviors and “sensory templates” because their forebears evolved to depend on many food sources. Similarly, “accurate throwing for hunting” may have promoted our human ancestor’s faculties. It is easy to neglect just how much planning, fine-motor control, and anticipation is necessary for such a feat.

Another important element for evolving intelligence appears to be social life and play. They provide social animals with opportunities to discover and hone new combinations. Social living also facilitates expanded behaviors as animals navigate group coordination and pecking orders. In this way, social intelligence confers evolutionary fitness by way of group survival and sexual selection. As Nicholas Humphrey writes in Consciousness Regained:

“Social primates are required by the very nature of the system they create and maintain to be calculating beings; they must be able to calculate the consequences of their own behavior, to calculate the likely behavior of others, to calculate the balance of advantage and loss—and all this in a context where the evidence on which their calculations are based is ephemeral, ambiguous and liable to change, not the least as a consequence of their own actions. In such a situation, ‘social skill’ goes hand in hand with intellect, and here at last the intellectual faculties required are of the highest order. The game of social plot and counter-plot cannot be played merely on the basis of accumulated knowledge… It asks for a level of intelligence which is, I submit, unparalleled in any other sphere of living.”
Nicholas Humphrey. (1984). Consciousness Regained.

Language trees and intelligence

For humans, language appears to be another base ingredient. If you think about it, language and intelligence appear to share many components. Both systems involve coding, decoding, meaning, construction, memory, organization, schema, and so on.

Wild chimpanzees can use around thirty-six different vocalizations to communicate things and actions. Humans, likewise, “have about three dozen units of vocalization”, Calvin explains. “But they’re all meaningless.” We combine syllables and phonemes to generate words, strings, sentences, analogies, ironies, and soliloquies. Unlike other social apes, language is an open-ended tree of possibilities for us humans. From quantum-gravity to non-Euclidean geometry, we seem to excel at sharing, stacking, and nurturing layer-upon-layer of cross-relations and abstract domains.

Unfortunately, “no one has yet explained how our ancestors got over the hump of replacing one-sound-[to]-one-meaning with a sequential combinatorial system of meaningless phonemes, but it’s probably one of the most important transitions that happened during ape-to-human evolution”, Calvin writes. What we do know, however, is that our propensity for language is assisted by “childhood acquisitiveness.” Language appears to come to children as naturally as does crawling and walking. This “tendency to discover and imitate order is so strong”, Calvin notes, “that deaf playmates may invent their own sign language with inflections if they aren’t properly exposed to one they can model.” This “pattern-seeking bioprogram” must be a building block of our intelligence.

Multipurpose brains

The interplay between language and intelligence should not strike us as far-fetched. Nature has a tendency to evolve functions that are later co-opted or “exapted” for other purposes. In A World Beyond Physics, Stuart Kauffman notes, for example, how our “middle ear bones, incus, malleus, and stapes evolved as exaptations from the jawbones of early fish.” Similarly, Raghu Garud explains that the “feathers [of birds] emerged to provide [them with] thermoregulation… [but] were later co-opted for catching insects… [and later] co-opted [again] for flight.”

Calvin suggests that the human brain was probably a product of a similar evolutionary process. Foresight, for instance, might be a by-product of advanced mental grammar, just as song and dance might be an outgrowth of our social “neural machinery”. Each region of the brain is multifunctional. The so-called language cortex, for example, is concerned not only with language but with sensation, movement, mimicry, and narrative. The brain resists simple labels.

Hierarchy and organization

Not only that, the brain resists reductionism too. From quantum interactions to chemical bonds to biochemistry to neural circuits, the brain exhibits several levels of self-organization. We will not find intelligence or consciousness by breaking the organ into its barest components. Seeking a chemical or quantum mechanical explanation is equivalent to staring from inside Plato’s Cave, says Calvin. “You start to interpret the shadows on the walls, making imperfect guesses about what’s really happening up there.” A satisfactory explanation demands an evolutionary and physiological approach on multiple floors.

Perhaps we might begin with the neuron—“the typical unit of computation.” A hundred of them make a minicolumn. And “roughly a hundred minicolumns [make] a macro-column”, while another “a hundred times a hundred macro-columns [make] a cortical area.” Add them up and you get “just over a hundred [of these] Brodmann Areas.” (One wonders if we can extend such multipliers further to separate brains—as we go from individuals to families to communities to nation states and international alliances.)

We realize, however, that simple aggregations like these are insufficient—for it is too much like an organizational chart of an immense company. They do not reveal the hidden networks, rules, feedback, and cross-connections that make the enterprise tick. “All of the interesting actions in the brain”, Calvin remarks, “involve spatiotemporal patterns of cellular activity”—“melodies of the cerebral cortex.” Intelligence and consciousness, he says, “is a process, not a place.”

Darwinian mind and cerebral codes

What then can we say about the patterns underway inside that noggin of ours? Calvin suspects that a Darwinian process, not unlike what we observe in nature and markets, apply. Certain patterns or ‘cerebral codes’ may represent specific things, associations, actions, abstractions, and modifiers. They can be chopped, meshed, joined, copied, combined, and so on. Such a mechanism, you can imagine, allows for bewildering possibilities and novelties. This may explain why we “can imagine a unicorn and form a memory of it”, Calvin notes.

You see, “the cortex is in the business of learning new patterns, whether sensory or movement, and creating variations on them.” Such variations, in turn, ‘compete’ for dominance in our limited workspace. “As you try to decide whether to pick an apple or a banana from the fruit bowl, the cerebral code for apple may have a cloning competition with the one for banana. When one code has enough active copies to trip the action circuits, you might reach for the apple”, Calvin writes. Multifaceted conditions by way of sensory-inputs, short- and long-term memories, emotional states, and so on, bias the “resonance possibilities” and competition that governs our patterns. In this way, thinking arises in part from a ceaseless jungle of cerebral code-copying competitions.

Synchronization and correction

Yet, when we stop to consider the orders-of-magnitude of organization inside the brain, and how complex the entire pattern-making enterprise must be, it is surprising that the system functions at all. Calvin agrees. The result to him, as a neurophysiologist, is “almost alarming”. One wonders “how runaway activity is reined in, [and] why seizures and hallucinations aren’t frequent events.” Calvin proposes that error-correction via ‘synchronization’ is at work. The process, he suggests, is akin to a choir in song. Rhythmic harmony is achieved because every singer is listening and adjusting to one another in concert. So “even if a neuron tries to do something different, it is forced back to the choral pattern that has become established by its insistent neighbors.” Such phase locking is not uncommon. Even “two identical pendulums will tend to synchronize if they are adjacent, just from the air and shelf vibrations they create”, Calvin reminds.

Metaphors and patchwork mosaics

You might find these metaphors unsatisfying. But until we further our mechanistic understanding of the brain, such relations may help us to grasp the essence of the complexity that beckons. The metaphor of a Darwinian Machine, Calvin believes, “bridges the gap between our perceived mental life and the neural mechanisms responsible for it.” It presents a way in which intelligent thought and creativity can arise from “chaotic neuron ensembles.”

Brains and intelligence remain nebulous things, of course. We know more about the Milky Way than we do about the Mind. Still, “you can get a feeling for what it’s like”, Calvin writes. “Looking down on the (virtually flattened) surface of the cortex would be like seeing a mosaic—a dynamic patchwork quilt… On closer inspection, each patch would appear like a wallpaper pattern that repeated… A twinkling spatiotemporal pattern.” This “shifting mosaic”, Calvin notes, is “a good candidate for intelligence.”

Sources and further reading

Calvin, William. (1996). How Brains Think.
Humphrey, Nicholas. (1984). Consciousness Regained.
Kauffman, Stuart. (2019). A World Beyond Physics.
Thomas, Lewis. (1974). The Lives of a Cell.
Krugman, Paul. (1995). The Self Organizing Economy.
Dyson, Freeman. (1988). Infinite in All Directions.
Ferris, Timothy. (1992). The Mind’s Sky.
Catmull, Ed., & Wallace, Amy. (2014). Creativity, Inc.
Garry, Kasparov. (2017). Deep Thinking.
Simon, Herbert. (1978). Rational Decision-Making.

How Brains Think — William Calvin on Intelligence and Darwinian Machines