The human brain is said to be the most complex object in the known universe. His 89 billion neurons each has around 7,000 connections on average, and the physical structure of all these entities may be precariously balanced on a knife’s edge, according to a new study.
Two physicists from Northwestern University in the US – Helen Ansell and István Kovács – have now used statistical physics to explain the complexity that can be seen in a highly detailed 3D map of not only part of the human brain, but also parts of the brain of a mouse and fruit fly. well.
At the cellular level, their framework suggests that the high-level hardware encapsulated in our skulls is in a structural sweet spot that closely approximates a phase transition.
“An everyday example of this is when ice melts into water. They’re still water molecules, but they’re going from a solid to a liquid,” explains Ansell.
“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 be transitioning between. Because if it was on either side of the critical point, it wouldn’t be a brain.”
In the past, some scientists suspected that phase transitions play an important role in biological systems. A good example is the membrane that surrounds cells. This lipid bilayer oscillates between a gel and liquid state to let proteins and fluid in and out.
In contrast, however, the central nervous system can balance on a critical point of transition without ever actually becoming anything else.
A common feature of this critical point is the branching structure of neurons, known as fractal patterns. Fractals, like those seen in snowflakes, moleculesor the distribution of galaxies, appear in it complex of systems. in physics, the fractal dimension is the “critical exponent” that sits on the edge of chaosbetween order and disorder.
Ansell and Kovác now claim that the presence of nanoscale fractals in 3D reconstructions of the brain is a sign of this “criticality”.
Due to data limitations, the duo was only able to analyze one partial region of the human, mouse and fruit fly brain. Yet even with this limited image, the team found matching fractal-like patterns that looked similar regardless of whether they were zoomed in or out.
The relative size of different neuronal segments and their diversity appear to be conserved across scales and species. Brain systems that are neither too organized nor too random are perfectly fine, balancing the cost of neural “wiring” with the demands of long-distance connections.
Ansell and Kovács argue that this ‘Goldilocks effect’ could be a universal, governing principle of all animal brains, although proving this will require much more research.
“At first, these structures look quite different – the fly’s entire brain is roughly the size of a small human neuron,” he says Ansell. “But then we found new properties that are surprisingly similar.”
Further studies are now needed to determine whether this shared criticality exists across the range of the animal brain and between different species.
While previous studies have analyzed the criticality of the brain in terms of neuron dynamicsit was not until recently possible to analyze and compare the structure of animal brains at the cellular level.
Of course, data limitations still exist, but there are currently major efforts in neuroscience to map the anatomy and connectivity of the brain in as many details as possible.
AND one cubic millimeter of the human brain was recently reconstructed and last year we have the first ever a complete map of the fruit fly brain, as well as a cellular map of the mouse brain.
“[The structural level] was the missing piece of how we think about the complexity of the brain,” he says physicist István Kovács from Northwestern.
“Unlike a computer, where any software can run on the same hardware, in the brain, dynamics and hardware are strongly related.”
Ansell he says the team’s findings “pave the way” to a simple physical model that can describe the brain’s statistical patterns. One day, such a feat could serve to improve brain research and train artificial intelligence systems.
The study was published in Communication physics.