Scientists Discover String Theory Explains Why Biological Networks Take Their Shape
For more than a hundred years, scientists have puzzled over why physical networks — such as blood vessels, neurons, tree branches and biological systems — take the shapes they do. The dominant idea was that nature designs these structures to be as efficient as possible, using the least amount of material. Yet repeated attempts to test this idea using standard mathematical optimization models consistently failed to match reality.
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A Shift in Perspective Solves a Century-Old Puzzle
The flaw, it seems, was a matter of perspective. Researchers were thinking in one dimension when the problem demanded three.
"We were treating these structures like wire diagrams," explains Rensselaer Polytechnic Institute physicist Xiangyi Meng, PhD. "But they are not thin wires—they are three-dimensional physical objects with surfaces that must join smoothly."
This month, Meng and his colleagues published a study in Nature revealing that living networks obey principles borrowed from an unexpected place: string theory, the branch of physics that seeks to explain the universe at its most fundamental level.
String Theory Finds a Surprising Role in Biology
The study marks the first time that string theory — a mathematical framework originally devised to unite quantum mechanics and gravity — has been used to successfully describe real biological structures. Although string theory remains unproven as a model of fundamental physics, its mathematics has proven surprisingly effective in explaining how living systems organize themselves in three-dimensional space.
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How String Theory Explains Branching in Living Systems
"There appears to be a universal rule that governs how biological networks form," Meng said. "It is a purely geometric optimization principle. It is indifferent to the type of material involved or the function being performed and it turns our to apply remarkably well across many different datasets."
In the 1980s, physicists grapping with the mathematics of vibrating strings in higher-dimensional space developed advanced techniques to calculate so-called "minimal surfaces" —the smoothest and most efficient ways to link object in space. Meng and his colleagues found that these same equations almost perfectly capture how biological networks reduce their material costs.
Why Traditional Models Fell Short
By contrast, traditional mathematical models tend to predict networks dominated by simple bifurcations, or two-way splits. Yet a glance at the branching patterns of a tree makes it clear that three-way, four-way and more complex junctions are widespread in a nature.
By contrast, the surface-minimization rules of string theory naturally permit these higher-order branch points. They also predict the presence of so-called "orthogonal sprouts" — thin, dead-end offshoots commonly seen in plants, neurons and other natural structures.
Orthogonal Sprouts and the Human Brain
In the human brain, around 98% of these perpendicular sprouts end in synapses, the crucial junctions where neurons connect.
These sprouts enable neurons to reach neighbouring cells while using the smallest possible amount of biological material. In much the same way, plant roots and fungal filaments grow perpendicular offshoots to explore soil more efficiently in search of water and nutrients.
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Testing the Theory Across Life Forms
The team put their theory to the test using high-resolution 3D scans of six very different network types:
- Neurons from humans
- Neurons from fruit flies
- Human blood vessels
- Tropical trees
- Corals
- Arabidopsis, a species of cress widely used in biological research
In every case, the observed branching patterns aligned more closely with surface-minimization predictions than with older models based purely on simple wiring efficiency.
Physics Meets Biology — With Limits
This does not suggest that physics alone dictates every detail of biological networks. Living systems operate under multiple competing constraints and the researchers found that real networks can be up to 25% longer than the theoretical minimum.
Even so, the striking consistency seen across such diverse organisms indicates that nature has settled on shared mathematical principles spanning the tree of life.
Implications for Science, Medicine and Engineering
"These results offer a compelling demonstration of how the abstract tools of theoretical physics can help address real-world challenges, including the exploration and understanding of connectivity patterns in the brain and in vascular systems." said Gyorgy Korniss, PhD, head of RPI's Department of Physics, Applied Physics and Astronomy.
In time, the findings could guide engineers in designing improved artificial networks, form 3D-printed tissues with functional blood vessels to more efficient transport systems. At a deeper level, the work highlights nature's remarkable efficiency: evolution often follows the same mathematical rules uncovered by physicists studying the structure of the universe.
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