One of the most popular explanations of human behavior has been that somewhere beneath our rational mind lurks an ancient “lizard brain”—a primitive evolutionary holdover responsible for instinct, emotion, fear, and aggression.

There is just one problem. Neuroscientists have long known that the lizard brain story is wrong. Humans did not evolve a sophisticated new brain by simply stacking it on top of an older reptilian one.

But a new study suggests the enduring lizard brain myth may have inadvertently pointed to something more interesting. Mammalian brains do appear to be organized around two broad computational systems—but not an ancient reptilian brain located beneath a newer, more sophisticated one. Instead, the divide appears to reflect two fundamentally different ways of organizing and processing information.

Published in Science Advances, the research combines anatomical measurements from 182 mammalian species with experiments using artificial neural networks. The researchers found a striking evolutionary trade-off between the neocortex and a collection of structures associated with smell, memory, and the limbic system.

Instead of representing “new” and “old” brains, the researchers say these regions may have evolved different wiring styles optimized for solving different kinds of computational problems.

“Rather than an ‘old’ brain and a ‘new’ brain, our results suggest two systems wired for different kinds of computation,” lead author Dr. Nabil Imam, a researcher at the Georgia Institute of Technology, told The Debrief. “The neocortex is wired to preserve spatial relationships—for example, neighboring points in the visual world are analyzed by neighboring parts of the cortex. The limbic system is more diffusely connected and supports holistic associations across different pieces of information.”

“So, the division between the neocortex and limbic system is about how the two systems are wired,” Dr. Imam added.

This distinction offers a very different picture from the famous lizard brain story.

The lizard brain concept grew from the so-called triune brain theory, which portrays the human brain as having evolved in distinct layers. A primitive “lizard brain” handling basic instincts, a mammalian limbic system producing emotion, and, finally, a newer neocortex responsible for higher thought.

The problem is that neuroscience has long since overturned that evolutionary story. Vertebrate brains did not evolve by progressively stacking newer brain regions on top of older, more primitive ones. Instead, vertebrates share essentially the same broad organizational plan, with existing regions changing in size, connectivity, and function over evolutionary time.

The new study suggests, however, that the mammalian brain may be divided very differently—not by evolutionary age, but by how different neural systems are wired to process information.

Across 182 species from 10 taxonomic groups, animals with an unusually large olfactory system tended to have a smaller-than-expected neocortex. Animals with an expanded neocortex tended to show the opposite pattern.

The nine-banded armadillo provides a particularly dramatic example. Armadillos are largely nocturnal and depend heavily on smell while foraging. As researchers note, the armadillo’s olfactory system was approximately 1.5 times larger than expected for its overall brain size. Its hippocampus—a region central to memory and spatial processing—was about twice its expected size.

Its neocortex, meanwhile, was reduced by a factor of 2.8. Primates such as squirrel monkeys sit closer to the other end of the spectrum. They rely heavily on vision and devote a large portion of their expanded neocortex to processing visual information.

At first glance, that could look like evolution trading smell for sight. But the researchers noticed something more intriguing. The hippocampus grew and shrank alongside the olfactory system, even though memory is obviously not another form of smell. Other structures traditionally grouped into the limbic system, including the amygdala and septum, also tended to change together.

That suggested the important difference might not be what these regions process, but how they are wired to process it.

Two Very Different Ways to Build a Brain

Vision offers a relatively straightforward example. Neighboring points in the visual world are generally processed through neighboring areas of the visual system. Touch operates similarly. Locations beside one another on your body retain spatial relationships as the nervous system processes them. Hearing also uses orderly mappings, including those based on sound frequency.

The result is what neuroscientists call “spatiotopic” organization. In simple terms, the brain preserves relationships between incoming information by arranging it into orderly maps.

However, smell works differently. Odors are represented through combinations of activity distributed across networks rather than being laid out in the same neat spatial fashion.

The researchers suspected that this difference might help explain the anatomical trade-off they had identified across mammals. To test the idea, they turned to artificial neural networks trained to handle vision, touch, hearing, and smell.

They then mapped the networks’ internal models onto artificial two-dimensional surfaces resembling sheets of cortex.

Results showed that networks optimized for vision, touch, and hearing produced smooth, highly ordered maps. On a scale in which 1 represented strong spatial order, the visual network scored 0.90, touch scored 0.86, and hearing scored 0.89.

Yet, the smell network scored just 0.11. Rather than producing a smooth map, information was scattered across a fractured, distributed representation. The researchers even found that imposing localized connectivity on the olfactory model harmed its ability to perform its task.

Researchers then examined memory. Using an artificial network designed to reproduce some relational computations associated with the hippocampus and entorhinal cortex, researchers again saw a fractured, distributed representation resembling the olfactory system rather than vision, hearing or touch.

For Dr. Imam, one of the most surprising results was that artificial networks arrived at an organization resembling real brains despite learning in profoundly different ways.

“Artificial networks are trained by an algorithm that propagates errors through the network, whereas brains are shaped by evolution and through localized changes in synapses,” Imam explained. “The fact that both nevertheless arrive at similar organization suggests that the structure of the information itself—whether visual, auditory, tactile, or olfactory—determines what kind of wiring works best.”

No “Lizard Brain,” But Evolution May Be Trading One Kind of Brainpower for Another

Researchers next wanted to know whether competition between these two wiring styles could reproduce the anatomical patterns seen across real mammals.

They created an evolutionary simulation containing five artificial networks. Vision, hearing, and touch occupied one computational domain based on localized, spatial organization. Smell and hippocampal memory occupied another based on distributed connectivity.

Then an evolutionary algorithm redistributed computational resources between them.

When selection favored vision, resources moved toward the spatially organized networks. When selection favored smell, the distributed networks expanded.

But something interesting occurred to the simulated hippocampal network. Even though researchers weren’t directly selecting for memory, the hippocampal network grew along with the olfactory network because both shared the same broad computational architecture. As resources shifted toward the other system, both contracted.

That closely resembled the pattern found across real mammalian brains.

“It suggests that evolution may not be selecting individual brain regions one at a time, but rather the functions produced by whole patterns of wiring,” Dr. Imam explained. “Because regions that share similar wiring tend to grow or shrink together, selection for one kind of function comes at the expense of another, given that the system must operate with limited energy and space.”

That does not mean an animal with a larger neocortex is simply more intelligent than one with a larger limbic system. Nor does the distributed system represent a primitive emotional brain fighting against a rational one.

Instead, the two architectures appear suited to different computational problems. Evolution may have repeatedly adjusted how much neural real estate mammals devote to each.

Nevertheless, researchers caution that their models are intentionally simplified. Anatomical measurements came from several datasets; some taxonomic groups are better represented than others, and artificial neural networks are not replicas of biological brains.

The evolutionary model is intended to demonstrate that a relatively simple developmental mechanism could produce the observed trade-off, not to reconstruct exactly how mammalian brains evolved.

Still, the research raises another interesting possibility extending beyond the demise of the “lizard brain.” Our brains may arrive in the world with considerably more computational structure already built in than the familiar idea of a blank slate implies.

“The brain may be much less of a blank slate than we often imagine,” Dr. Imam told The Debrief. “Evolution and development build useful assumptions into its wiring before experience-driven learning.”

It is also another example of something scientists are increasingly encountering across very different areas of biology: evolution can produce remarkably sophisticated structures and systems that human engineers are just starting to understand, much less reproduce.

In a recent study covered by The Debrief, researchers discovered that cable bacteria construct microscopic electrical pathways from nickel-rich nanoribbons arranged remarkably like braided electrical wires. The naturally grown structures may achieve extraordinary conductivity while remaining flexible, properties that researchers are now interested in replicating for bio-based electronics.

The mammalian brain represents an enormously more complicated example, but the underlying lesson may be similar. Evolution does not begin with a blank slate each generation. It can build useful solutions into biological architecture itself, leaving subsequent learning along with adaptation to operate within structures refined over immense spans of evolutionary time.

That could also help explain one of the most striking differences between biological intelligence and today’s artificial intelligence. Modern AI systems can require enormous datasets to acquire abilities that biological brains learn from comparatively limited experience.

“That built-in structure may explain why brains can learn efficiently from relatively little experience, whereas most artificial networks require enormous datasets to learn useful functions,” Imam said. “The idea has deep roots in philosophy of mind, but only recently have neuroscience and computer science begun to provide concrete demonstrations of how such built-in structure can aid function.”

The recent study, “Dual computational systems in the development and evolution of mammalian brains,” appeared in Science Advances.

Tim McMillan is a retired law enforcement executive, investigative reporter and co-founder of The Debrief. His writing typically focuses on defense, national security, the Intelligence Community and topics related to psychology. You can follow Tim on Twitter: @LtTimMcMillan.  Tim can be reached by email: tim@thedebrief.org or through encrypted email: LtTimMcMillan@protonmail.com 

Scientists have theorized for decades about how the human brain evolved and grew dramatically in size. Now, new research points to one common ingredient that may have played a crucial role in the brain’s evolution over time: sugar.

A research team at the University of Sydney and the University of Glasgow created a model comparing modern nutrition with that of our ancestors over a span of four million years. The findings suggest that our ancestors relied on naturally occurring carbohydrate-rich foods, which could have played an important role in not only their overall dietary nutrition but also the evolution of the human brain.

These new findings challenge an older scientific model that emphasizes meat as a primary driving force behind human evolution.

“Raw starch does not release glucose, meaning early humans likely relied on naturally sweet foods long before grains became a regular part of the diet,” said lead author Professor Jennie Brand-Miller, Professor of Human Nutrition at the University of Sydney Charles Perkins Center and School of Life and Environmental Sciences, in a statement. 

While meat played a role in our ancestors’ diets, the new research suggests that the amount of energy required by a growing brain also needs to be considered. Throughout human evolution, brain size increased from roughly 300 grams in early hominins to approximately 1,500 grams in modern humans. Glucose is the brain’s primary energy source, creating increasing nutritional demands as brain size grew over time.

“While animal foods were important, the brain’s need for glucose has largely received little attention from anthropologists,” Professor Brand-Miller said.  

The Research

To better understand this hypothesis, the team created a model encompassing six evolutionary stages. Researchers estimated the “obligatory glucose demand” of the brain and other glucose-dependent tissues, including red blood cells, kidneys, and reproductive tissues. They then compared these glucose requirements with the carbohydrate sources that would have been readily available to humans during different stages of evolution.

“The human brain is unusually large for our body size and requires substantial amounts of energy,” Professor Brand-Miller said.  “Glucose is the brain’s primary energy source, and for much of human evolution, would have come from carbohydrates found in foods such as fruit and honey.” 

The model incorporated evidence from numerous fields, including metabolism, food composition, fossil isotope studies, dental morphology, archaeology, primate diets, and genetics.

Overall, the research suggests that early hominins, including Australopithecus, Homo habilis, and Homo erectus, were highly dependent on carbohydrate-rich foods, with fruit representing an important source. Later, as humans began using fire to cook food, starch-rich plants could also provide significant amounts of glucose. Grains, meanwhile, appear to have entered the human diet much later. The researchers point to archaeological evidence of seed grinding dating to around 65,000 years ago.

“People often think of carbohydrates as breads and cereals, but for most of human evolution carbohydrates came from fruits, honey and underground plant foods,” said Professor Brand-Miller. “The earliest evidence of seed grinding is 65,000 years ago, when we see the first evidence of grinding stones to make flour.” 

The study also examined the role of glucose in reproduction and pregnancy. Pregnancy and lactation significantly increase glucose demands, since energy is required not only by the mother but also by the developing fetus and placenta, as well as for milk production.

The new findings may also help explain humans’ longstanding attraction to sweet foods. For much of human evolution, naturally sweet foods such as fruit and honey provided concentrated sources of energy while also supplying fiber, vitamins, minerals, and other nutrients.

That doesn’t mean people should start making a run for the candy aisle. The findings do not suggest that modern humans should consume more refined sugar. Instead, the researchers distinguish between naturally occurring sugars found in whole foods and highly processed foods containing large quantities of added sugar.

Sugar was also not the human brain’s only source of fuel, nor were carbohydrates the sole dietary factor influencing human evolution. Rather, the researchers argue that glucose requirements have often received less attention than other dietary factors, including meat, fat, and protein. Our ancient appetite for naturally sweet, carbohydrate-rich foods, however, may have helped fuel the extraordinary expansion of the human brain.

Chrissy Newton is a PR professional and the founder of VOCAB Communications. She currently appears on The Discovery Channel and Max and hosts the Rebelliously Curious podcast, which can be found on YouTube and on all audio podcast streaming platforms. Follow her on X: @ChrissyNewton, Instagram: @BeingChrissyNewton, and chrissynewton.com. To contact Chrissy with a story, please email chrissy @ thedebrief.org.