For over a century, researchers have thought that the patterns of brain activity that define our experiences, hopes, and dreams are determined by how different brain regions communicate with each other through a complex web of trillions of cellular connections.
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 (1✔ ✔Trusted Source
Eigenmodes of brain activity: Neural field theory predictions and comparison with experiment
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). This work focused on developing the best way to efficiently construct the eigenmodes of the brain.
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The eigenmodes of the brain are determined by their structural physical, geometric, and anatomical properties, but which specific properties are most important has remained a mystery.
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.
They 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 that it can make (2✔ ✔Trusted Source
Cortical geometry as a determinant of brain activity eigenmodes: Neural field analysis
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Using mathematical models, they 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.
These findings open opportunities to understanding 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.
The research team found that, across over 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 mm (3✔ ✔Trusted Source
Geometric constraints on human brain function
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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.
References :
- Eigenmodes of brain activity: Neural field theory predictions and comparison with experiment – (https://www.sciencedirect.com/science/article/abs/pii/S1053811916300908)
- Cortical geometry as a determinant of brain activity eigenmodes: Neural field analysis
– (https://journals.aps.org/pre/abstract/10.1103/PhysRevE.96.032413) - Geometric constraints on human brain function – (https://www.nature.com/articles/s41586-023-06098-1)
Source: Eurekalert
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