Resume: New research shows that brain structures in humans, mice and fruit flies are near a phase transition, suggesting a universal principle. The study found that brain cells exhibit fractal patterns, indicating criticality.
This discovery could improve computational models of brain complexity. The findings highlight a new dimension in understanding brain dynamics and structure.
Key Facts:
- Brain structures in humans, mice and fruit flies are showing signs of criticality.
- Fractal-like patterns in brain cells suggest a phase transition state.
- The study’s findings could lead to improved models of brain complexity.
Source: Northwestern University
When a magnet is heated, it reaches a critical point where it loses magnetization. This point of high complexity is called ‘criticality’ and is reached when a physical object transitions smoothly from one stage to the next.
Now, a new study from Northwestern University has found that the structural features of the brain are near a similar critical point – at or near a structural phase transition. Surprisingly, these results are consistent across the brains of humans, mice and fruit flies, suggesting the finding could be universal.
Although the researchers don’t know between which stages the brain’s structure is, they say this new information could enable new designs for computational models of the brain’s complexity and emergent phenomena.
The research was published today (June 10) in Communications Physics, a journal published by Nature Portfolio.
“The human brain is one of the most complex systems known, and many properties of the details that determine its structure are not yet understood,” said István Kovács of Northwestern, senior author of the study.
“Several other researchers have studied brain criticality in terms of neuron dynamics. But we look at criticality at the structural level to ultimately understand how this supports the complexity of brain dynamics.
“That has been a missing piece in the way we think about the complexity of the brain. Unlike a computer where all software can run on the same hardware, in the brain the dynamics and the hardware are strongly connected.”
“The structure of the brain at the cellular level appears to be near a phase transition,” said Helen Ansell of Northwestern, the paper’s first author.
“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.
We’re certainly not saying that the brain is about to melt. In fact, we have no way of knowing between which two phases the brain might be. Because if it were on either side of the critical point, it wouldn’t be a brain.”
Kovács is an assistant professor of physics and astronomy at Northwestern’s Weinberg College of Arts and Sciences. At the time of the study, Ansell was a postdoctoral researcher in his laboratory; now she is a Tarbutton Fellow at Emory University.
Although researchers have long studied brain dynamics using functional magnetic resonance imaging (fMRI) and electroencephalograms (EEG), advances in neuroscience have only recently produced massive data sets for the brain’s cellular structure.
These data opened up opportunities for Kovács and his team to apply statistical physics techniques to measure the physical structure of neurons.
For the new study, Kovács and Ansell analyzed publicly available data from 3D brain reconstructions of humans, fruit flies and mice. By examining the brain at nanoscale resolution, the researchers found that the samples showed signatures of physical properties associated with criticality.
One of those properties is the well-known, fractal-like structure of neurons. This non-trivial fractal dimension is an example of a set of observables, called ‘critical exponents’, that arise when a system is close to a phase transition.
Brain cells are arranged in a fractal-like statistical pattern at different scales. When zoomed in, the fractal shapes are “self-similar,” meaning smaller parts of the sample resemble the entire sample. The sizes of the different neuron segments observed are also diverse, providing another clue.
According to Kovács, self-similarity, long-range correlations, and wide size distributions are all features of a critical state, in which features are neither too organized nor too random. These observations lead to a series of critical exponents that characterize these structural features.
“These are things we see in all critical systems in physics,” Kovács said. “It seems that the brain is in a delicate balance between two phases.”
Kovács and Ansell were surprised to find that all brain samples studied – from humans, mice and fruit flies – have consistent critical exponents for all organisms, meaning they share the same quantitative characteristics of criticality.
The underlying compatible structures between organisms indicate that a universal principle of governance may be at play. Their new findings may help explain why brains from different creatures share some of the same fundamental principles.
“Initially, these structures look very different: an entire fly brain is about the size of a small human neuron,” Ansell said. “But then we found emerging properties that are surprisingly similar.”
“Of the many features that are very different between organisms, we relied on the suggestions of statistical physics to check which measurements are potentially universal, such as critical exponents. These are indeed consistent across all organisms,” Kovács said.
“As an even deeper sign of criticality, the critical exponents obtained are not independent – for any three we can calculate the rest, as dictated by statistical physics.
“This finding opens the way to formulating simple physical models to capture statistical patterns of brain structure. Such models are useful input for dynamic brain models and can be inspiring for artificial neural network architectures.”
Next, the researchers plan to apply their techniques to new data sets, including larger parts of the brain and more organisms. They want to find out whether universality still applies.
The study, “Revealing Universal Aspects of Brain Cellular Anatomy,” was supported in part by the computing resources of the Quest high-performance computing facility at Northwestern.
About this neuroscience research news
Author: Amanda Morris
Source: Northwestern University
Contact: Amanda Morris – Northwestern University
Image: The image is credited to Neuroscience News
Original research: Open access.
“Revealing Universal Aspects of the Cellular Anatomy of the Brain” by István Kovács et al. Communication physics
Abstract
Revealing universal aspects of the cellular anatomy of the brain
Recent volumetric brain reconstructions at the cellular level have revealed a high degree of anatomical complexity. Determining which structural aspects of the brain to focus on, especially compared to computer models and other organisms, remains a major challenge.
Here we quantify aspects of this complexity and show evidence that brain anatomy obeys universal scaling laws, establishing the idea of structural criticality in the brain’s cellular structure.
Our framework builds on the understanding of critical systems to provide clear guidance in selecting informative structural properties of cellular brain anatomy.
To illustrate, we obtain estimates for critical exponents in the brains of humans, mice, and fruit flies and show that these are consistent across organisms as data limitations permit.
Such universal quantities are robust to many of the microscopic details of the cellular structures of individual brains, and represent an important step toward generative computational models of the brain’s cellular structure, as well as clarifying in what sense one animal is an appropriate anatomical can be a model for another.