HomePOPULARPhysicists Discover Fractal Patterns in Brain Structure, Hinting at Universal Principles

Physicists Discover Fractal Patterns in Brain Structure, Hinting at Universal Principles

The human brain is said to be the most complex object in the known universe. Each of the 89 billion neurons has an average of about 7,000 connections, and according to this research, the physical structure of these entities can be compared to the edge of a knife.

Two physicists from Northwestern University, Helen Ansell and Istvan Kovacs, have now used statistical physics to explain the complexity of not only the human brain, but also a part of the mouse and fruit fly brain, shown in a very detailed 3D map. good

At the cellular level, the framework suggests that our head-mounted high-level devices are in the structural sweet spot approaching the phase transition.

“The daily example is ice melting into ice. It’s still water molecules, but it’s going from solid to liquid,” Ansell explained.

“Of course, we’re not saying that our brains are melting. We don’t really know what two phases our brains can go between. Because if they are on both sides of the critical point, it won’t be ‘Don’t be a brain!’ “

In the past, some scientists doubted that phase transitions play an important role in biological systems. A good example is the cell membrane. This lipid bilayer alternates between a gel and liquid state to allow proteins and fluids to enter and exit.

On the contrary, the central nervous system may be the most important point of transition, but in reality it becomes nothing more.

A common feature of this important point is the branch-like structure of neurons known as fractal patterns. Patterns seen in snowflakes, molecules, or the distribution of galaxies occur in the most complex systems. In physics, the fractal dimension is the “critical exponent” that lies on the edge of chaos between chaos and disorder.

Ansell and Kovacs now claim that the nanoscale presence of fractals in 3D brain reconstructions is a sign of this “significance”.

Due to limited data, the team was only able to analyze partial brains of humans, mice and fruit flies. However, with these limited images, the team found the same fractal-like patterns regardless of whether they were zoomed in or out.

The relative size and diversity of different neuronal segments appear to be conserved across scales and species. Neither systematic nor random, the brain system perfectly balances the cost of proper neural wiring with the demands of long-distance connections.

Ansell and Kovacs suggest that the Goldilocks effect may be universal, the principle governing all animal brains, although they argue that more research is needed.

“At first glance, this structure is very different—the entire brain of a fly is roughly the size of a small human neuron,” Ansell said. “But then we found the same emerging characteristics.”

Further research is now needed to determine whether this general criticism exists in animal brains and across species.

Although previous studies have analyzed the importance of the brain in terms of neuronal dynamics, it has not been possible until now to analyze and compare the structure of the animal brain at the cellular level.

Of course, there are data limitations, but there is currently a large-scale effort in neuroscience to map the brain’s anatomy and connections as much as possible.

Recently, cubic millimeters of the human brain have been reconstructed, and last year we obtained the first complete map of the fruit fly brain, as well as the cellular map of the mouse brain.

“[The level of structure] has been missing from how we think about the complexity of our brains,” says Northwestern physicist Istvan Kovač.

“Unlike a computer where any software can run on the same machine, the dynamics of the brain and the machine are very tightly coupled.”

Ansell said the team’s findings “pave the way” to simple physical models that can explain statistical patterns of the brain. One day, such achievements could be used to improve brain research and train artificial intelligence systems. The research was published in Physical Communications.

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