A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains

by Max Solomon Bennett

The human brain contains eighty-six billion neurons and over a hundred trillion connections. Each of those connections is so minuscule—less than thirty nanometers wide—that they can barely be seen under even the most powerful microscopes. These connections are bunched together in a tangled mess—within a single cubic millimeter (the width of a single letter on a penny), there are over one billion connections.

What is most striking when we examine the brains of other animals is how remarkably similar their brains are to our own. The difference between our brain and a chimpanzee’s brain, besides size, is barely anything. The difference between our brain and a rat’s brain is only a handful of brain modifications. The brain of a fish has almost all the same structures as our brain.

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.

Even after the discovery of evolution, the idea of a scale of nature continues to persist. This idea that there is a hierarchy of species is dead wrong. All species alive today are, well, alive; their ancestors survived the last 3.5 billion years of evolution. And thus, in that sense—the only sense that evolution cares about—all life-forms alive today are tied for first place.

Life on Earth fell into perhaps the greatest symbiosis ever found between two competing but complementary systems of life, one that lasts to this day. One category of life was photosynthetic, converting water and carbon dioxide into sugar and oxygen. The other was respiratory, converting sugar and oxygen back into carbon dioxide. At the time, these two forms of life were similar, both single-celled bacteria. Today this symbiosis is made up of very different forms of life. Trees, grass, and other plants are some of our modern photosynthesizers, while fungi and animals are some of our modern respirators.

Respiratory microbes differed in one crucial way from their photosynthetic cousins: they needed to hunt. And hunting required a whole new degree of smarts.

This is the most shocking observation when comparing neurons across species—they are all, for the most part, fundamentally identical. The neurons in the human brain operate the same way as the neurons in a jellyfish. What separates you from an earthworm is not the unit of intelligence itself—neurons—but how these units are wired together.

While plants survive by photosynthesis, animals and fungi both survive by respiration. Animals and fungi both breathe oxygen and eat sugar; both digest their food, breaking cells down using enzymes and absorbing their inner nutrients; and both share a much more recent common ancestor than either do with plants, which diverged much earlier. At the dawn of multicellularity, fungi and animal life would have been extremely similar. And yet one lineage (animals) went on to evolve neurons and brains, and the other (fungi) did not. Why?

Fungi eat through external digestion (secreting enzymes to break food down outside the body), while animals eat through internal digestion (trapping food inside the body and then secreting enzymes).

Fungi produce trillions of single-celled spores that float around dormant. If by luck one happens to find itself near dying life, it will blossom into a large fungal structure, growing hairy filaments into the decaying tissue, secreting enzymes, and absorbing the released nutrients. This is why mold always shows up in old food. Fungal spores are all around us, patiently waiting for something to die.

Animals uniquely form little stomachs where they trap prey, secrete enzymes, and digest them.

A coral polyp is, in some sense, literally only a stomach with neurons and muscles. They have little tentacles that float in the water, waiting for small organisms to swim toward them. When food touches one of the tips of these tentacles, they rapidly contract, pulling the prey into the stomach cavity where it is digested. Neurons on the tips of these tentacles detect food and trigger a cascade of signaling through a web of other neurons that generates a coordinated relaxing and contracting of different muscles.

The first discovery was that neurons don’t send electrical signals in the form of a continuous ebbing and flowing but rather in all-or-nothing responses, also called spikes or action potentials. A neuron is either on or off; there is no in between. In other words, neurons act less like an electric power line with a constant flow of electricity and more like an electric telegraph cable, with patterns of electrical clicks and pauses.

It turned out the spikes were identical in all cases; the only difference was how many spikes were fired. The heavier the weight, the higher the frequency of spikes (figure 1.9). This was Adrian’s second discovery, what is now known as rate coding. The idea is that neurons encode information in the rate that they fire spikes, not in the shape or magnitude of the spike itself. Since Adrian’s initial work, such rate coding has been found in neurons across the animal kingdom, from jellyfish to humans. Touch-sensitive neurons encode pressure in their firing rate; photosensitive neurons encode contrast in their firing rate; smell-sensitive neurons encode concentration in their firing rate. The neural code for movement is also a firing rate: the faster the spikes of the neurons that stimulate muscles, the greater the contraction force of the muscles.

Neurons do not have a fixed relationship between natural variables and firing rates. Instead, neurons are always adapting their firing rates to their environment; they are constantly remapping the relationship between variables in the natural world and the language of firing rates. The term neuroscientists use to describe this observation is adaptation; this was Adrian’s third discovery.

In the 1950s, John Eccles discovered that neurons come in two main varieties: excitatory neurons and inhibitory neurons. Excitatory neurons release neurotransmitters that excite neurons they connect to, while inhibitory neurons release neurotransmitters that inhibit neurons they connect to. In other words, excitatory neurons trigger spikes in other neurons, while inhibitory neurons suppress spikes in other neurons.

These features of neurons—all-or-nothing spikes, rate coding, adaptation, and chemical synapses with excitatory and inhibitory neurotransmitters—are universal across all animals, even in animals that have no brain, such as coral polyps and jellyfish.

While the first animals, whether gastrula-like or polyp-like creatures, clearly had neurons, they had no brain. Like today’s coral polyps and jellyfish, their nervous system was what scientists call a nerve net: a distributed web of independent neural circuits implementing their own independent reflexes.

There is another observation about bilaterians, perhaps the more important one: They are the only animals that have brains. This is not a coincidence. The first brain and the bilaterian body share the same initial evolutionary purpose: They enable animals to navigate by steering. Steering was breakthrough #1.

And so we begin with the simplest two features of emotions, those that are universal not only across human cultures but also across the animal kingdom, those features of emotions that we inherited from the first brains: valence and arousal.

Dopamine drives the hunt for food; serotonin drives the enjoyment of it once it is being eaten.

Dopamine is not a signal for pleasure itself; it is a signal for the anticipation of future pleasure.

serotonin is the satiation, things-are-okay-now, satisfaction chemical, designed to turn off valence responses.

There are additional neuromodulators, equally ancient, that undergird the mechanisms of negative affect—of stress, anxiety, and depression.

Adrenaline not only triggers the behavioral repertoire of escape; it also turns off a swath of energy-consuming activities to divert energetic resources to muscles. Sugar is expelled from cells across the body, cell growth processes are halted, digestion is paused, reproductive processes are turned off, and the immune system is tamed. This is called the acute stress response—what bodies do immediately in response to negative-valence stimuli.

Any consistent, inescapable, or repeating negative stimuli, such as constant pain or prolonged starvation, will shift a nematode brain into a state of chronic stress. Chronic stress isn’t all that different from acute stress; stress hormones and opioids remain elevated, chronically inhibiting digestion, immune response, appetite, and reproduction. But chronic stress differs from acute stress in at least one important way: it turns off arousal and motivation.

This is called spontaneous recovery: broken associations are rapidly suppressed but not, in fact, unlearned; given enough time, they reemerge. Further, if after a long stretch of trials with a broken association (buzzer but no food), you reinstate the association (sound a buzzer and provide food again), the old association will be relearned far more rapidly than the first time the dog experienced the association between the buzzer and food. This is called reacquisition: old extinguished associations are reacquired faster than entirely new associations.

Eligibility traces, overshadowing, latent inhibition, and blocking are ubiquitous across Bilateria. Pavlov identified these in the conditional reflexes of his salivating dogs; they are found in the involuntary reflexes of humans; and they are seen in the associative learning of flatworms, nematodes, slugs, fish, lizards, birds, rats, and most every bilaterian in the animal kingdom. These tricks for navigating the credit assignment problem evolved as far back as the very first brains to make associative learning work.

Learning occurs when synapses change their strength or when new synapses are formed or old synapses are removed. If the connection between two neurons is weak, the input neuron will have to fire many spikes to get the output neuron to spike. If the connection is strong, the input neuron will have to fire only a few spikes to get the output neuron to spike. Synapses can increase their strength by the input neuron releasing more neurotransmitter in response to a spike or the postsynaptic neuron increasing the number of protein receptors (hence more responsive to the same quantity of neurotransmitter).

Learning was not the core function of the first brain; it was merely a feature, a trick to optimize steering decisions. Association, prediction, and learning emerged for tweaking the goodness and badness of things.

The brains of all vertebrate embryos, from fish to humans, develop in the same initial steps. First, brains differentiate into three bulbs, making up the three primary structures that scaffold all vertebrate brains: a forebrain, midbrain, and hindbrain. Second, the forebrain unfolds into two subsystems. One of these goes on to become the cortex and the basal ganglia, and the other goes on to become the thalamus and the hypothalamus.

The circuitry of the human basal ganglia, thalamus, hypothalamus, midbrain, and hindbrain and that of a fish are incredibly similar.

The second breakthrough was reinforcement learning: the ability to learn arbitrary sequences of actions through trial and error.

The neocortex is continuously comparing the actual sensory data with the data predicted by its simulation. This is how you can immediately identify anything surprising that occurs in your surroundings.

While damage to the aPFC deprives animals of their intentions, as we saw with patient L, damage to parts of the premotor cortex seems to disconnect the proper flow of these intentions from high-level goals to specific movements. This can cause “alien limb syndrome”: patients will claim that certain parts of their bodies are moving on their own without their control. Signs of such alien movements are also seen in rodents with damage to the premotor cortex. Such damage also causes what is called “utilization behavior” or “field-dependent behavior,” where patients will execute motor sequences devoid of any clear goal: They will drink from empty cups, put on other people’s jackets even though they aren’t going anywhere, scribble with pencils, or do any other behavior that nearby stimuli suggest. All this is the result of a broken hierarchy—parts of the motor cortex are now unconstrained by top-down intentions from the aPFC flowing through the premotor cortex, and hence the motor cortex independently sets low-level goals for motor sequences.

The aPFC and sensory neocortex worked together to enable early mammals to pause and simulate aspects of the world that were not currently being experienced—in other words, model-based reinforcement learning.

In later mammals, the motor cortex evolved, enabling mammals to plan and simulate specific body movements.

Understanding the minds of others requires understanding not only their intentions but also their knowledge.

It isn’t clear how political savviness would even be possible if a species did not have at least a basic and primitive version of theory of mind—only through this ability can individuals infer what others want and thereby figure out whom to cozy up to and how. Only through theory of mind can individual primates know not to mess with a low-ranking individual with high-ranking friends; this requires understanding the intent of the high-ranking individuals and what they will do in future situations. Only through this ability of theory of mind can you figure out who is likely to become powerful in the future, whom you need to make friends with, and whom you can deceive.

What is the most natural activity we use language for? Well, we gossip. We often can’t help ourselves; we have to share moral violations of others, discuss relationship changes, keep track of dramas. Dunbar measured this—he eavesdropped on public conversations and found that as much as 70 percent of human conversation is gossip. This, to Dunbar, is an essential clue into the origins of language.

Breakthrough #1 was steering:

Breakthrough #2 was reinforcing:

Breakthrough #3 was simulating:

Breakthrough #4 was mentalizing:

Breakthrough #5 was speaking:

Each breakthrough was possible only because of the building blocks that came prior. Steering was possible only because of the evolution of neurons earlier. Reinforcement learning was possible only because it bootstrapped on the valence neurons that had already evolved: without valence, there is no foundational learning signal for reinforcement learning to begin. Simulating was possible only because trial-and-error learning in the basal ganglia existed prior. Without the basal ganglia to enable trial-and-error learning, there would be no mechanism by which imagined simulations could affect behavior; by having actual trial-and-error learning evolve in vertebrates, vicarious trial and error could emerge later in mammals. Mentalizing was possible only because simulating came before; mentalizing is just simulating the older mammalian parts of the neocortex, the same computation turned inward. And speaking was possible only because mentalizing came before; without the ability the infer the intent and knowledge in the mind of another, you could not infer what to communicate to help transmit an idea or infer what people mean by what they say. And without the ability to infer the knowledge and intent of another, you could not engage in the crucial step of shared attention whereby teachers identify objects for students.