Biological systems are notoriously tough to model, especially when it comes to figuring out the axons, neurons, blood vessels, and other structural components of gray matter, or the tissue that makes up your nervous system. The human brain is the largest of any primate, and it’s built to store and process information. However, how our brain is put together has been difficult to figure out thus far—but we may have a new trick.
Published January 7 in the journal Nature, one paper tackled the age-old problem of nature’s construction with a bit of a twist: it suggests that living networks, like our brain, may use some of the structural rules of string theory, a theoretical physics framework. In other words, there may be analogies between how subatomic particles make up our universe and how the brain evolved. The team cautions that the research doesn’t necessarily address how we think, but rather how the brain is put together.
String theory is a mathematical construct that meshes Einstein’s theory of general relativity with quantum mechanics, or the behavior of subatomic particles. While scientists have so far had trouble verifying string theory through observation, the idea is that these tiny particles that make up the entire universe are actually sort of “stringlike.” We interpret these strings’ vibrations as matter like electrons or atoms. In other words, string theory is scientists’ best stab at a theory of everything.
So what does this theory have to do with the brain? According to the research team, vibrating strings can also be used to calculate something called “minimal surfaces,” which is the easiest way to connect objects together. It tentatively appears that biological networks like the brain may be built the same way, according to the team.
“We want to study all those [biological] networks and actually go up into the construction” of the brain, says Xiangyi Meng, PhD, lead author of the recent study and a physicist at Rensselaer Polytechnic Institute. “For that, you need temporal data instead of just topological structures … A string theory based approach also predicts how [the structures are] going to grow up, like how they develop branches.”
With older mathematical techniques (which Meng said in some cases, had roots from a century ago), models of branches of structures in the brain—such as nerves—had a bias toward two-way splits. However, it’s common for more complex splits to happen in nature. For instance, looking at a tree branch often shows branches coming out in three ways, four ways, or more.
String theory, Meng’s team says, can even account for “orthogonal sprouts,” which are dead ends that naturally appear on trees, plants, and the neurons of brains. In brains, synapses—or connection points between neurons—occur in 98 percent of these sprouts. That’s important because the neuron connections aim to use as little biological material as they can to save on energy. Plants and fungi do the same thing with their roots, in search of the water and nutrients in soil.
The idea that sting theory can predict the brain’s structure is still an early notion, and not everything necessarily falls under quantum physics. The study considered not only neurons and blood vessels in humans, but also trees, corals, Arabidopsis plants, and even fruit fly neurons. String theory suggested that minimal surfaces are present in these various systems, but in reality, the networks appear to be at least 25 percent longer than theory would predict.
Meng also cautioned that, as a paper focused on nature’s structures, it would be difficult to make leaps to the theory of consciousness, or how the brain constructs reality.
“We are not saying that the brain is quantum,” says Meng, noting that not all aspects of string theory would be likely to fit biological systems. Rather, the research “is really about the mathematical structure developed by string theories … they can be used to describe the fundamental universe, but at least some parts of the math can be used to describe biology.”
Vijay Balasubramanian, PhD, a biophysicist at the University of Pennsylvania who is not involved in the research, said the paper has some benefit to the field.
“I think that the positive contribution of this paper is to recognize that the surface area of neurons and their axons is probably more important than their length in determining the best structure to achieve the necessary function,” he says. “They used a piece of mathematics about minimal surfaces with some constraints. Apparently the mathematics was worked out in string theory, so they borrowed that formalism.”
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Balasubramanian, who studies self-organization and information processing by natural systems, said the paper makes a contribution to the study of the structure of physical networks. Work has been done in this field before, he pointed out, and said that he would love to see more work on “explanations and theory of how and why such structures arise.”
Meng added that the research is ongoing, as the team is planning to do a series of papers. As the research proceeds, team members plan to deepen collaborations with neuroscientists for future publications. (They have already been in discussion with Princeton University, for example.)
He emphasized the team is going to look at structures in higher-resolution to continue to understand how they were made, and to make predictions about how they have evolved. But for now, the blueprint for our squishy control centers remains ones of nature’s great mysteries.
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Elizabeth Howell (Ph.D., she/her) is one of a few space journalists in Canada. She has written five books, and was Space.com’s former staff reporter in spaceflight. As a freelancer, she has written or edited articles about astronomy and space exploration for outlets such as Payload Space, Air&Space Magazine, Sky & Telescope and Salon. Elizabeth holds university degrees in journalism, science and history and also teaches an astronomy course, with Indigenous content, at Canada’s Algonquin College. Aside from watching several astronaut missions launching from Florida and Kazakhstan, Elizabeth once lived like an astronaut at the Mars Society’s Mars Desert Research Station in Utah.