New research by scientists at the University of Sydney and Monash University has shown that the overall shape and geometry of a person’s brain – its contours and curvature – exerts a greater influence on the brain’s dynamics than the internal connectivity of brain cells.
This finding published today in Nature counters the conventional wisdom that emphasises the importance of complex brain connectivity between neurons.
The joint team led by Monash University’s Turner Institute and School of Psychological Sciences ARC Laureate Fellow Professor Alex Fornito examined more than 10,000 different maps of human brain activity to reach its findings.
Co-lead author, Dr Kevin Aquino of BrainKey AI and an honorary research fellow at the University of Sydney School of Physics, said: “Just as the resonant frequencies of a violin string are determined by its length, density and tension, the eigenmodes – or oscillating frequencies – of the brain are determined by its structural properties – physical, geometric and anatomical; but which specific properties are most important has remained a mystery until now.”
Joint lead author and Research Fellow Dr James Pang, from the Turner Institute and Monash University’s School of Psychological Sciences, said the findings were significant because they could simplify the way that we can study how the brain functions, develops and ages.
“The work opens opportunities to understand the effects of diseases like dementia and stroke by considering models of brain shape, which are far easier to deal with than models of the brain’s full array of connections,” said Dr Pang, who did his PhD at the University of Sydney.
“We have long thought that specific thoughts or sensations elicit activity in specific parts of the brain, but this study reveals that structured patterns of activity are excited across nearly the entire brain, just like the way in which a musical note arises from vibrations occurring 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 all excited at the same frequency. Eigenmodes are normally used to study physical systems in areas such as physics and engineering and have only recently been adapted to study the brain.
The team compared how well eigenmodes obtained from models of the shape of the brain could account for different patterns of activity when compared to eigenmodes obtained from models of brain connectivity.
“We found that eigenmodes defined by brain geometry – its contours and curvature – represented the strongest anatomical constraint on brain function, much like the shape of a drum influences the sounds it can make,” Professor Fornito said.
“Using mathematical models, we confirmed theoretical predictions that the close link between geometry and function is driven by wave-like activity propagating throughout the brain, just as the shape of a pond influences the wave ripples that are formed by a falling pebble,” he said.
“These findings raise the possibility of predicting the function of the brain directly from its shape, opening new avenues for exploring how the brain contributes to individual differences in behaviour and risk for psychiatric and neurological diseases.”
The theoretical foundations for this experimental research were developed over decades in the School of Physics at the University of Sydney in work led by Professor Peter Robinson.
Dr Ben Fulcher, who leads the Dynamics and Neural Systems Group in the School of Physics and co-author on the paper, said: “This work underscores the importance of collaboration across scientific disciplines – in this case between physics and neuroscience.
“By analysing the brain as a physical system we were able to capture and understand patterns hidden in its incredible complexity.”
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 that have very long wavelengths, extending over distances exceeding 40 millimetres.
“This result counters conventional wisdom, in which activity during different tasks is often assumed to occur in focal, isolated areas of elevated activity, and tells us that traditional approaches to brain mapping may only show the tip of the iceberg when it comes to understanding how the brain works,” Dr Pang said.
This work was supported by the MASSIVE HPC facility, Sylvia and Charles Viertel Foundation, National Health and Medical Research Council, Australian Research Council.
Dr Kevin Aquino is a scientific adviser and shareholder in BrainKey Inc, a medical image analysis software company. The other authors declare no competing interests.