Unlocking the Relationship between Brain Shape and Function
For more than a century, scientists believed that the brain’s connectivity patterns determined our experiences, hopes, and dreams. However, recent research from Monash University’s Turner Institute for Brain and Mental Health suggests that the overall shape of a person’s brain has greater influence over how we think, feel, and behave than its intricate neural connections. The research team examined over 10,000 different maps of human brain activity, revealing that structured patterns of activity are activated almost throughout the entire brain, similar to how a musical note emerges from vibrations along the entire length of a violin string.
Eigenmodes: The Natural Patterns of Vibration or Excitation
The research team used magnetic resonance imaging (MRI) to study eigenmodes, which are the natural patterns of vibration or excitation in a system, where different parts are excited at the same frequency. Eigenmodes are similar to the resonant frequencies of a violin string, which are determined by length, density, and tension. The team developed a way to efficiently build the eigenmodes of the brain, comparing how well eigenmodes obtained from brain shape models could explain different activity patterns compared to eigenmodes obtained from brain connectivity models. They found that the eigenmodes defined by the brain’s geometry, its contours and curvature, represented the strongest anatomical constraint on brain function.
The Brain’s Geometry and Function
The link between geometry and function is driven by wave-like activity that propagates throughout the brain. The research team discovered that activity was dominated by eigenmodes with spatial patterns having lengths very long waves, which extend to distances greater than 40 mm, across over 10,000 MRI activity maps. This finding contradicts conventional wisdom, in which activity during different tasks is often assumed to occur in isolated, focal areas of elevated activity. Additionally, the researchers used mathematical models to confirm theoretical predictions, raising the possibility of predicting brain function directly from its shape, opening up new avenues to explore how the brain contributes to individual differences in behavior and risk of psychiatric and neurological diseases.
Impact on Brain Research and Understanding Diseases
The study led by Monash University’s Turner Institute for Brain and Mental Health represents significant simplification in studying how the brain functions, develops and ages, as it offers new ways of understanding the effects of diseases such as dementia and stroke through considering models of the shape of the brain. The findings also provide insight into how the brain contributes to individual differences in behavior and psychiatric/ neurological diseases.
Expanding on the Topic
As technology continues to advance, enhancing the accuracy and capabilities of MRI scans, the possibilities of unlocking the relationship between brain function and geometry expand. The medical field is already using 3D printing technology to create replicas of patients’ brains to aid in surgical planning for complex neurosurgeries. The ratio of a person’s brain size to their body size, known as the Encephalization Quotient (EQ), has long been studied by researchers, with findings suggesting a positive correlation between EQ and intelligence. Additionally, AI technology is being developed that can predict a person’s mental health status from their brain scan results. This technology could have significant impacts on early detection and treatment of psychiatric diseases such as depression, anxiety, and PTSD.
Enhancing the accuracy of eigenmode models could also have implications for the development of intelligent machines. As scientists work on understanding the connection between geometry and function in the brain, they can apply similar theories to developing intelligent machines. By understanding the structure and patterns of the brain that generate particular behaviors, scientists may be able to replicate those patterns in machines and create more capable, efficient, and intelligent AI systems.
Summary
Traditional brain research emphasized complex neural connectivity’s importance to determine the patterns of brain activity that define our experiences, hopes, and dreams. However, the overall shape of the brain has greater influence over how we think, feel, and behave than its intricate neural connections, according to recent research from Monash University’s Turner Institute for Brain and Mental Health. The research team examined over 10,000 different maps of human brain activity and developed a way to efficiently build the eigenmodes of the brain, revealing that structured patterns of activity are activated almost throughout the entire brain. The link between brain geometry and function is driven by wave-like activity that propagates throughout the brain. The research team discovered that activity was dominated by eigenmodes with spatial patterns having lengths very long waves, which extend to distances greater than 40 mm, across over 10,000 MRI activity maps. This finding contradicts conventional wisdom, in which activity during different tasks is often assumed to occur in isolated, focal areas of elevated activity. The study has significant implications for brain research, disease understanding, and the development of intelligent machines.
—————————————————-
| Article | Link |
|---|---|
| UK Artful Impressions | Premiere Etsy Store |
| Sponsored Content | View |
| 90’s Rock Band Review | View |
| Ted Lasso’s MacBook Guide | View |
| Nature’s Secret to More Energy | View |
| Ancient Recipe for Weight Loss | View |
| MacBook Air i3 vs i5 | View |
| You Need a VPN in 2023 – Liberty Shield | View |
For more than a century, researchers have believed that the patterns of brain activity that define our experiences, hopes, and dreams are determined by how different regions of the brain communicate with one another through a complex network of trillions of cellular connections.
Now, a study led by researchers at Monash University’s Turner Institute for Brain and Mental Health has examined more than 10,000 different maps of human brain activity and found that the overall shape of a person’s brain greatly influences greater in how we think, feel, and behave than its intricate neural connectivity.
The study, published today in the journal, Nature brings together approaches from physics, neuroscience, and psychology to reverse the centuries-old paradigm that emphasizes the importance of complex brain connectivity, rather than identifying a previously unnoticed relationship between brain shape and activity.
Lead author and researcher Dr James Pang, from the Turner Institute and Monash University School of Psychological Sciences, said the findings were significant because they vastly simplified the way we can study how the brain functions, develops and ages. brain.
“The work opens up opportunities to understand the effects of diseases such as dementia and stroke by considering models of the shape of the brain, which are much easier to handle than models of the full range of brain connections,” said Dr. .pang.
“We have long thought that specific thoughts or sensations trigger activity in specific parts of the brain, but this study reveals that structured patterns of activity are activated in almost the entire brain, much like the way a musical note emerges from vibrations that occur along the entire length of a violin string, and not just an isolated segment,” he said.
The research team used magnetic resonance imaging (MRI) to study eigenmodes, which are the natural patterns of vibration or excitation in a system, where different parts of the system are excited at the same frequency. Eigenmodes are commonly used to study physical systems in areas such as physics and engineering and have only recently been adapted to study the brain.
This work focused on developing the best way to efficiently build the eigenmodes of the brain.
“Just as the resonant frequencies of a violin string are determined by its length, density, and tension, the eigenmodes of the brain are determined by its structural properties (physical, geometric, and anatomical), but the specific properties that are most important are have remained … a mystery,” said co-lead author Dr. Kevin Aquino, of BrainKey and the University of Sydney.
The team, led by ARC Laureate Fellow of the Turner Institute and School of Psychological Sciences, Professor Alex Fornito, compared how well eigenmodes obtained from models of brain shape could explain different activity patterns compared to eigenmodes obtained from brain models. connectivity.
“We found that the eigenmodes defined by the brain’s geometry, its contours and curvature, represented the strongest anatomical constraint on brain function, just as the shape of a drum influences the sounds it can make,” said Professor Fornito. .
“Using mathematical models, we confirm theoretical predictions that the tight link between geometry and function is driven by wave-like activity that propagates throughout the brain, just as the shape of a pond influences waves of wave formed when a pebble falls,” he said. saying.
“These findings raise the possibility of predicting brain function directly from its shape, opening up new avenues to explore how the brain contributes to individual differences in behavior and risk of psychiatric and neurological diseases.”
The research team found that across more than 10,000 MRI activity maps, obtained as people performed different tasks developed by neuroscientists to probe the human brain, activity was dominated by eigenmodes with spatial patterns having lengths very long waves, which extend to distances greater than 40 mm.
“This result contradicts conventional wisdom, in which activity during different tasks is often assumed to occur in isolated, focal areas of elevated activity, and tells us that traditional approaches to brain mapping may only show the tip of the iceberg when it’s about understanding how the brain works,” said Dr. Pang.
https://www.sciencedaily.com/releases/2023/05/230531150131.htm
—————————————————-