The human brain is It is said to be The most complex body in the known universe. that it 89 billion neurons Each has about 7,000 connections on average, and the physical structure of all those entities may be precariously balanced on a knife-edge, according to a new study.
Physicists at Northwestern University in the US – Helen Ansel and Istvan Kovacs – used statistical physics to explain the complexity seen in a highly detailed 3D map of not only part of the human brain, but also part of the brains of mouse and fruit flies. Good.
At the cellular level, their framework suggests that the higher-level organs encased in our skulls are at a structurally fine point closely approaching a transitional stage.
“An everyday example of this is when ice melts in water. They are still water molecules, but they are going through a solid-to-liquid transition.” He explains Ancel.
“We’re certainly not saying the brain is about to melt. In fact, we have no way of knowing which two phases the brain might transition between. Because if it were on either side of the critical point, that wouldn’t be the case.” Not the brain.”
Some scholars have questioned this in the past Phase transitions It plays an important role in biological systems. The membrane that surrounds cells is a good example. This lipid bilayer fluctuates between a gel and liquid state to allow proteins and liquid to move in and out.
In contrast, the central nervous system may oscillate at a critical transition point, while never turning into something else.
The common feature of this critical point is the branch-like structure of neurons, known as Fractal patterns. Fractals, such as those seen in snowflakes, Moleculesor the distribution of galaxies, appears in most of them Systems complex. in physics, The fractional dimension is the “critical exponent” that lies on The edge of chaosBetween order and chaos.
Ansell and Kovach now argue that the presence of nanoscale fractals in 3D brain reconstructions is a sign of this “criticality.”
Due to data limitations, the duo was only able to analyze only one partial region of the human, mouse and fruit fly brain. However, even with this limited image, the team found identical fractal-like patterns that look similar regardless of whether they are zoomed in or out.
The relative size and diversity of different neuronal segments appears to be conserved across scales and species. Neither too organized nor too random are brain systems, they are just right, balancing the costs of neural “wiring” with the demands of long-distance communications.
The “Goldilocks effect” could be a universal principle governing all animal brains, Ansel and Kovacs say, though proving this will require more research.
“At first, these structures look very different – the entire fly brain is roughly the size of a small human neuron.” He says Ancel. “But then we found surprisingly similar emergent properties.”
Further studies are now needed to determine whether this common importance exists across the full range of the animal brain and between different species.
While previous studies have analyzed the importance of the brain when it comes to… Neuronal dynamicsUntil recently, it has not been possible to analyze and compare the structure of animal brains at the cellular level.
Of course, there are still data limitations, but there are currently large-scale efforts in neuroscience to map the anatomy and connections of the brain. As much detail as possible.
a One cubic millimeter A human brain was recently reconstructed, and last year, We got our first ever A complete map of the fruit fly brain, plus… Cellular map of the mouse brain.
“[The structural level] “It was a missing piece to how we think about brain complexity.” He says Physicist Istvan Kovacs of Northwestern.
“Unlike a computer where any program can run on the same hardware, dynamics and hardware are closely linked in the brain.”
Ancel He says The team’s findings “open the way” to a simple physical model that can describe statistical patterns of the brain. One day, this breakthrough could be used to improve brain research and train artificial intelligence systems.
The study was published in Communications physics.
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