The human brain does Said to be the most complex object in the known universe. Are 89 billion neurons each has an average of about 7,000 connections, and the physical structure of all these entities may be teetering dangerously on a razor’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 seen in a highly detailed 3D map of not only part of the human brain, but also of part of the brain of mice and fruit flies. Good.
At the cellular level, their framework suggests that the high-quality hardware encapsulated in our skulls is in a structural sweet spot that is close to a phase transition.
‘An everyday example of this is when ice melts in water. They are still water molecules, but they are undergoing a transition from solid to liquid,’ explains Ansell.
‘We are certainly not saying that the brain is almost melting. In fact, we have no way of knowing between which two phases the brain might be. not being a brain.”
In the past, some scientists have suspected that phase transitions play an important role in biological systems. The membrane that surrounds cells is a good example. This lipid bilayer fluctuates between gel and liquid states to allow proteins and liquids in and out.
In contrast, however, the central nervous system can falter at a critical transition point, never really becoming anything else.
A 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, is most prominent complex of systems. In physics, the fractal dimension is a “critical exponent” located on the edge of chaosbetween order and disorder.
Ansell and Kovác now argue that the presence of nanoscale fractals in 3D brain reconstructions is a sign of this ‘criticality’.
Due to data limitations, the duo were only able to analyze one partial brain region from a human, a mouse and a fruit fly. But even with this limited view, the team found matching fractal-like patterns that looked the same regardless of whether they zoomed in or out.
The relative sizes of different neuron segments and their diversity appear to persist across scales and species. The brain’s systems are neither too organized nor too random. They weigh the costs of neural ‘wiring’ against the requirements of long-distance connections.
This “Goldilocks effect” could well be a universal, guiding principle of all animal brains, Ansell and Kovács argue, although they prove that much more research is needed.
“Initially, these structures look very different: an entire fly brain is about the size of a small human neuron,” say Ansell. “But then we found emerging properties that are surprisingly similar.”
Further studies are now needed to determine whether that shared critique exists across the full scale of the animal brain and across species.
While previous studies have analyzed the brain criticality when it comes to neuron dynamicsUntil recently, it was not possible to analyze and compare the structure of animal brains at the cellular level.
Of course, data limitations still exist, but there is currently extensive work in neuroscience to map the anatomy and connections of the brain. as much detail as possible.
a several cubic millimeters of a human brain was recently reconstructed, and last year we have the very first ever complete map of a fruit fly’s brain, as well as a cellular map of the mouse brain.
“[The structural level] has been a missing piece in the way we think about the complexity of the brain.” say physicist István Kovács from Northwestern.
“Unlike a computer where all software can run on the same hardware, in the brain the dynamics and the hardware are strongly linked.”
Ansell say The team’s findings “open the way” to a simple physical model that can describe statistical patterns of the brain. One day, such an achievement could be used to improve brain research and train artificial intelligence systems.
The research was published in Communication physics.