Today's Reading
In evolution, systems start simple, and complexity emerges only over time. The first brain—the first collection of neurons in the head of an animal—appeared six hundred million years ago in a worm the size of a grain of rice. This worm was the ancestor of all modern brain-endowed animals. Over hundreds of millions of years of evolutionary tinkering, through trillions of small tweaks in wiring, her simple brain was transformed into the diverse portfolio of modern brains. One lineage of this ancient worm's descendants led to the brain in our heads.
If only we could go back in time and examine this first brain to understand how it worked and what tricks it enabled. If only we could then track the complexification forward in the lineage that led to the human brain, observing each physical modification that occurred and the intellectual abilities it afforded. If we could do this, we might be able to grasp the complexity that eventually emerged. Indeed, as the biologist Theodosius Dobzhansky famously said, "Nothing in biology makes sense except in the light of evolution."
Even Darwin fantasized about reconstructing such a story. He ends his 'Origin of Species' fantasizing about a future when "psychology will be based on a new foundation, that of the necessary acquirement of each mental power and capacity by gradation." One hundred fifty years after Darwin, this may finally be possible.
Although we have no time machines, we can, in principle, engage in time travel. In just the past decade, evolutionary neuroscientists have made incredible progress in reconstructing the brains of our ancestors. One way they do this is through the fossil record— scientists can use the fossilized skulls of ancient creatures to reverse-engineer the structure of their brains. Another way to reconstruct the brains of our ancestors is by examining the brains of other animals in the animal kingdom.
The reason why brains across the animal kingdom are so similar is that they all derive from common roots in shared ancestors. Every brain in the animal kingdom is a little clue as to what the brains of our ancestors looked like; each brain is not only a machine but a time capsule filled with hidden hints of the trillions of minds that came before. And by examining the intellectual feats these other animals share and those they do not, we can begin to not only reconstruct the brains of our ancestors, but also determine what intellectual abilities these ancient brains afforded them. Together, we can begin to trace acquirement of each mental power by gradation.
It is all, of course, still a work in progress, but the story is becoming tantalizingly clear.
The Myth of Layers
I am hardly the first to propose an evolutionary framework for understanding the human brain. There is a long tradition of such frameworks. The most famous was formulated in the 1960s by the neuroscientist Paul MacLean. MacLean hypothesized that the human brain was made of three layers (hence 'triune'), each built on top of another: the 'neocortex', which evolved most recently, on top of the 'limbic system', which evolved earlier, on top of the 'reptile brain,' which evolved first.
MacLean argued that the reptile brain was the center of our basic survival instincts, such as aggression and territoriality. The limbic system was supposedly the center of emotions, such as fear, parental attachment, sexual desire, and hunger. And the neocortex was supposedly the center of cognition, gifting us with language, abstraction, planning, and perception. MacLean's framework suggested that reptiles had 'only' a reptile brain, mammals like rats and rabbits had a reptile brain 'and' a limbic system, and we humans had all three systems. Indeed, to him, these "three evolutionary formations might be imagined as three interconnected biological computers, with each having its own special intelligence, its own subjectivity, its own sense of time and space, and its own memory, motor, and other functions."
The problem is that MacLean's Triune Brain Hypothesis has been largely discredited—not because it is inexact (all frameworks are inexact), but because it leads to the wrong conclusions about how the brain evolved and how it works. The implied brain anatomy is wrong; the brains of reptiles are not only made up of the structures MacLean referred to as the "reptile brain"; reptiles also have their own version of a limbic system. The functional divisions proved wrong; 'survival instincts, emotions,' and 'cognition' do not delineate cleanly—they emerge from diverse networks of systems spanning all three of these supposed layers. And the implied evolutionary story turned out to be wrong. You do not have a reptile brain in your head; evolution did not work by simply layering one system on top of another without any modifications to the existing systems.
But even if MacLean's triune brain had turned out to be closer to the truth, its biggest problem is that its functional divisions aren't particularly useful for our purposes. If our goal is to reverse-engineer the human brain to understand the nature of intelligence, MacLean's three systems are too broad and the functions attributed to them too vague to provide us with even a point at which to start.
We need to ground our understanding of how the brain works and how it evolved in our understanding of how intelligence works—for which we must look to the field of artificial intelligence. The relationship between AI and the brain goes both ways; while the brain can surely teach us much about how to create artificial humanlike intelligence, AI can also teach us about the brain. If we think some part of the brain uses some specific algorithm but that algorithm doesn't work when we implement it in machines, this gives us evidence that the brain might not work this way. Conversely, if we find an algorithm that works well in AI systems, and we find parallels between the properties of these algorithms and properties of animal brains, this gives us some evidence that the brain might indeed work this way.
The physicist Richard Feynman left the following on a blackboard shortly before his death: "What I cannot create, I do not understand." The brain is our guiding inspiration for how to build AI, and AI is our litmus test for how well we understand the brain.
We need a new evolutionary story of the brain, one grounded not only in a modern understanding of how brain anatomy changed over time, but also in a modern understanding of intelligence itself.
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