4/25 The Brain as a Super Universe
Introduction to the Brain as a Super Universe
Shall I compare thee to a summer’s day? Thou art more lovely and more temperate… So begins Sonnet 18 by William Shakespeare. In this week’s lesson, we are comparing two things, but summer is not one of them. We will be looking at comparisons that have been made between the Universe and our brain. And then, for the purpose of comparison, we will look at past comparisons between the brain and the computer. Which do you think will make a better comparison?
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Shall I compare thee to a summer's day?
Introduction to mapping the universe
(Engelking, 2014) (Space.com staff, 2014) (Tate, 2014) (Rundle, 2013)
Technology is an amazing thing. With computer simulations, imaging methods like MRI and high power telescopes, we are now offered a unique view of things which we have only imagined in the past. It was sometime around 2014 that researchers began to use computer simulations to visualize the birth of our universe. Just prior to this, physicists suggested that the universe may be growing in the same way as a giant brain, which led to the use of simulations. The simulation, called Illustris, begins just 12 million years after the Big Bang and illustrates the formation of stars, heavy elements, galaxies, exploding supernovae and dark matter over the 14 billion years that follow.
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The video which uses computer simulations, imaging methods and high power telescopes to capture the growth of the universe.
It took five years to program Illustris and took 8,000 CUPs running in unison for three months to crunch all of the numbers. It would have taken an average desktop computer over 2,000 years to complete the calculations. Previous simulations were limited by computing power, and either focused on a very small corner of the universe or displayed the results in low resolutions. This tool can study “cosmic phenomena”, such as galaxy formation at specific points in history.
The simulation of the evolution of the universe lets scientists see the dark matter density field, gas temperatures and gas metallicity in a cube measuring about 350 million light years on each side. (source)
The largest structures in the known universe are the galaxy filaments or “great walls” of galaxy superclusters. The filaments form the boundaries between great voids in space. It is believed by scientists that the galaxy filaments form along a web-like distribution of dark matter, the dominant form of matter in the universe.
Scientist Karl Tate took these images and created detailed information on how the universe was modeled, based on these computer simulations. He created an infographic which summarizes what he has discovered. Here is what he created: (3 diagrams) (source)
Introduction to Brain Imaging
(The History of MRI, 2015) (Portnow, 2013) (What Is an Electron Microscope (EM) and How Does It Work?, 2017) (Fonta, 2015)
The functional organization of the human brain has been speculated since the 1800s when the physiology of brain circulation first became appreciated. The evolution from theory to medical practice did not occur until the 1950s when modern radiotracers and technologically advanced scanning devices were introduced. PET imaging paved the way for understanding how the brain behaves. It was invented in 1975, and ultimately developed into a working prototype in 1997.
PET scanner
MRI imaging was introduced in 1979 and was used in 1982 to measure blood oxygen levels. By 1987, brain function was found to be related to MRI changes, and oxygen was introduced as a contrast agent during MRI. In 1991 fMRI imaging began in humans. Soon after, research centers, hospitals, and even small remote hospitals and imaging centers began to use MRI for neuroimaging and musculoskeletal imaging.
MRI scanner
The signals obtained with PET and fMRI are based on changes in blood flow, oxygen consumption and glucose utilization. It creates a surprisingly precise way to study the cellular activity of the brain. The brain imaging reveals blood flow in the brain in relationship to cellular activity.
Another imaging tool, designed to capture the structure and composition of a cell is the Electron Microscope. These use a focused beam of electrons instead of photons to “image” the specimen and gain information. Acute brain slices can be studied under the Electron microscope to provide a clearer picture of the brain cells, and particularly the microglia, astrocytes, neurons and their communication.
Electron microscope
The comparison: Neuronal networks and the Universe
(Vazza, 2020) (Starr, 2020)
In 2020, a paper by astrophysicist Franco Vazza and neurosurgeon Alberto Feletti was released illustrating the similarities between the network of neuronal cells in the human brain and the cosmic network of galaxies. Exploring the structural, morphological, network properties and the memory capacity, the systems were compared with a quantitative approach.
The human brain: The human brain is a complex structure with cellular, molecular and neuronal components. It is a hierarchical network, where neurons cluster into circuits, columns and different functional areas. The structure of the neuronal network allows linking between different areas.
The universe: The universe is comprised of self-gravitating dark matter dominated halos, where ordinary matter has created galaxies (and stars within them). Galaxies can group into huge structures, called clusters, superclusters and filaments. Gravity accelerates matter at these boundaries to speed thousands of km/second, creating shock waves and turbulence in intergalactic gases.
The two structures differ in size by 27 orders of magnitude (billion billion billion). But this research suggests that although the physical processes that drive the universe and the brain are extremely different, they can result in similar levels of complexity and self-organization.
Vazza and Feletti began their work by looking at the similarities between the two:
· The human cerebellum has about 69 billion neurons, while the cosmic web contains over 100 billion galaxies.
· Both are organized in well-defined networks with nodes (neurons in the brain, galaxies in the universe) connected via filaments.
· Both neurons and galaxies have a typical scale radius that is only a fraction of the length of the filaments. And the flow of energy between nodes is only around 25% of the mass and energy content of each system.
· There is also the composition of each. Each has a large proportion of its matter as passive. The brain is around 77% water, while the universe is around 68% dark energy. These passive materials seem to play only an indirect role in their internal structure.
After coming up with the similarities, they began to quantitatively compare the two, based on images. They took slices of the human cerebellum and cortex at different magnifications and compared them to simulations of the cosmic web. They were looking for similarities in the matter density changes between the brain and the universe. They found that these fluctuations were amazingly similar, although on very different scales.
Things that were observed by Vazza and Feletti during their analysis:
· The fluctuation within the cerebellum neuronal network was seen on a scale from 1 micrometer to .1 mm. This follows the same progression of matter in the universe, but on a much larger scale (5 million to 500 million light-years).
· They also looked at the number of filaments connected to each node. The cosmic web had an average of 3.8 to 4.1 connections per node, while the human cortex had an average of 4.6 to 5.4 connections per node.
· They found that both systems seemed to cluster connections around central nodes. And both seem to have a similar information capacity. (Studies suggest that the memory of the human brain is around 2.5 petabytes, while the memory capacity of the universe is around 4.3 petabytes. Researchers have suggested that this similarity in memory capacity means that the entire body of information stored in a human brain (the entire life experience of a person) can be encoded into the distribution of galaxies in our universe.
They concluded that the two complex networks show more similarities than when comparisons are made between the cosmic web and a galaxy or between a neuronal network and the inside of a neuron.
What is dark energy and dark matter?
(Lindsey, 2022) (Betz, 2020)
Our lesson mentions dark energy and dark matter. These are two starkly different components of the universe.
Dark matter slows the expansion of the universe. It works like an attractive force, a cosmic cement holding the universe together. It interacts with gravity, but does not reflect, absorb or emit light.
Dark energy is a repulsive force, sort of anti-gravity, which drives the universe’s ever accelerating expansion.
Dark energy is more dominant, making up roughly 68% of the universe’s total mass and energy. Dark matter makes up 27%, while the rest (about 5%) is the regular matter we see and interact with each day.
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Dark matter and dark energy explained in simple terms.
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From Ted Ed, another short video explaining dark matter and dark energy.
Although the existence of dark matter is widely accepted, for decades physicists have tried to use high-tech instruments to find signs of it. So far, they have not been successful. This is because tools used to measure dark energy and matter in the universe (electromagnetic radiation, gravitational effects, compared against other matter with strong nuclear force, or comparing the subatomic particles when there is weak nuclear force) do not seem to work, as dark matter does not appear to interact with standard matter at all, except through gravity. This may change, as technologies improve for measuring dark matter and energy.
So, what exactly is dark matter? One thing that physicists have discovered is that it appears to be a form of matter from an entirely different class or classes of subatomic particle, perhaps one known as WIMP. This is just one of the many theories on what dark matter is comprised of. Further complicating the matter is the fact that researchers at Yale have found two galaxies that don’t have any dark matter at all.
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How do they measure dark matter? This video describes.
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How can we find the WIMP particles? Interesting panel.
Dark energy has been observed for many years, as astronomers noticed galaxies moving away from each other. This phenomenon is what provided evidence for the Big Bang Theory. At one point, scientists believed that the gravitational pull of the cosmos stars and galaxies should be slowing down the universe’s expansion, and that it could ultimately collapse into a Big Crunch. However, in the late 1990s, two teams of astronomers discovered that distant galaxies were moving away from us faster than nearby galaxies. The universe wasn’t just expanding, it was speeding up.
Of course, dark energy and dark matter are theories, and not widely understood. Some physicists think that there is an entire dark realm of particles and forces out there, playing tug-of-war with the universe.
Universe expands over time
Another common comparison: Brain vs Computer
(Chudler, 2020) (Difference Between Brain and Computer, 2021)
Although comparing the brain neural network to the universe is somewhat new, for years there has been a comparison between the brain and the computer. Much has been written about this, with evidence supporting and rejecting the comparison. Let’s consider some of what has been said.
Some basic similarities between the brain and a computer:
Communication: Both use electrical signals to send messages
Transmitting information: Both transmit information
Memory: Both can grow memory
Learning: Both can adapt and learn
Evolution: Both have evolved over time
Energy: Both need energy to exist
Damage risk: Both can be damaged
Modification: Both can be changed and modified
Math: Both can do math and other logical tasks
Research: Both are studied by scientists
Key differences between the brain and computer:
Memory: Although both can grow their memory, memory in the brain grows instantly by synaptic links, where in a computer a chip must be added
Communication: Although they both use electrical signals, the brain produces weak electrical signals through chemicals exchanged between neurons, while the computer generates electrical signals of higher power.
Backup: The brain as an inbuilt backup system where functioning pathways replace damaged pathways. Backup systems are constructed manually in a computer.
Energy: The energy consumption is the brain is less than the computer
Storing information: The brain stores information in electrochemical and electromagnetic form. The computer stores information in symbolic and numeric form.
Transmitting information: In the brain, chemicals assist in firing action potentials in the neurons. The computer uses electrically coded signals to transmit data
Processing power: The processing power of the brain is unlimited and provides online processing, but information is processed slower because neurons are slow in action. Computers process information much faster because of fast transitions.
Organization: The brain is self-organized while the computer is preprogrammed structure.
Ability to understand: Some of you might disagree, but a computer is easy to understand by opening it up. There are still many unknowns and questions about the brain.
On/Off: You can turn off a computer, but you cannot turn off the brain.
Updates: You can update a computer (expand memory, replace processor) but not the brain.
Video:
A visual guide to the similarities and differences between the brain and the computer.
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Can you build a computer like a brain? The term is: neuromorphic computing.
How can this lesson improve your brain health?
Unlike lessons with clear examples of how to benefit brain health, this lesson does not seem to follow our conventional rules. There is no suggestion that a healthy diet, brain training exercises, socialization, exercise and more will improve our understanding of the structural makeup between the universe and the brain.
However, this lesson can work subtly with you. By taking you beyond your comfort zone (physics, really?), you are faced with a different perspective. You are asked to compare these two seemingly different things and perhaps when your brain sees the comparison, you might get a spark of dopamine. Understanding this lesson challenges your brain. It is progressive, in that you see the image, then read the lesson, then view videos. Each level increases the connections in the brain. Perhaps you will tell others about this fascinating topic. In this case, you will have to verbalize what you have learned, and find a way to explain to others.
So, the value of this lesson to your brain is intellectual challenge. Embrace the opportunity to increase connections in your brain and strive to understand the concepts of the lesson. In this way, our lesson on the brain and the universe will spark your brain and create new connections. Good luck!
Summary:
Although this lesson may have challenged some of us, especially those of us with poor physics understanding, it did provide a chance to look at the brain’s neural circuit from another perspective. It is amazing how similar the two systems are (brain vs universe). Science has created technologies in understanding both of them. What is the possible application of this understanding? Is it possible that the brain’s neural circuit evolved based on the general layout of the universe? Do the similarities suggest a common thread? Now that the connection has been established, it will be interesting to see if physicists and neuroscientists can use this information to better understand the universe and brain. But for now, let the computer/brain comparison rest. The brain is not a computer.
Works Cited
Betz, E. (2020, March 3). What's the difference between dark matter and dark energy? Retrieved from astronomy.com: https://astronomy.com/news/2020/03/whats-the-difference-between-dark-matter-and-dark-energy
Chudler, E. (2020, March). The Brain vs. The Computer. Retrieved from faculty.washington.edu: https://faculty.washington.edu/chudler/bvc.html
Difference Between Brain and Computer. (2021, June). Retrieved from techdifferences.com: Difference Between Brain and Computer
Engelking, C. (2014, May 7). Evolution of the Universe Revealed in Computer Simulation. Retrieved from discovermagazine.com: https://www.discovermagazine.com/the-sciences/evolution-of-the-universe-revealed-in-computer-simulation
Fonta, C. e. (2015, January). Analysis of acute brain slices by electron microscopy: a correlative light-electron microscopy workflow based on Tokuyasu cryo-sectioning. Retrieved from pubmed.ncbi.nlm.nih.gov: https://pubmed.ncbi.nlm.nih.gov/25448886/
Lindsey, J. (2022, March 23). Filling the Void: What Is Dark Matter? Retrieved from popularmechanics.com: https://www.popularmechanics.com/space/deep-space/a27560790/what-is-dark-matter/
Portnow, L. e. (2013, March 5). The history of cerebral PET scanning. Retrieved from ncbi.nlm.nih.gov: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3653214/
Rundle, M. (2013, January 26). Physicists Find Evidence That The Universe Is A 'Giant Brain'. Retrieved from huffingtonpost.co.uk: https://www.huffingtonpost.co.uk/2012/11/27/physicists-universe-giant-brain_n_2196346.html
Space.com staff. (2014, May 7). Evolution of the Universe Revealed by Computer Simulation (Gallery). Retrieved from sapce.com: https://www.space.com/25777-universe-evolution-simulation-images-gallery.html
Starr, M. (2020, November 17). Study Maps The Odd Structural Similarities Between The Human Brain And The Universe. Retrieved from sciencealert.com: https://www.sciencealert.com/wildly-fun-new-paper-compares-the-human-brain-to-the-structure-of-the-universe
Tate, K. (2014, May 7). How Computers Simulate the Universe. Retrieved from space.com: https://www.space.com/25793-universe-evolution-model-infographic.html
The History of MRI. (2015, January). Retrieved from two-views.com: https://two-views.com/mri-imaging/history.html
Vazza, F. a. (2020, November 16). The Quantitative Comparison Between the Neuronal Network and the Cosmic Web. Retrieved from frontiersin.org: https://www.frontiersin.org/articles/10.3389/fphy.2020.525731/full
What Is an Electron Microscope (EM) and How Does It Work? (2017, August 1). Retrieved from va.gov: https://www.va.gov/DIAGNOSTICEM/What_Is_Electron_Microscopy_and_How_Does_It_Work.asp