Unlocking the Secrets of the Brain’s Cleaning System

Imagine a system within our brains that tirelessly works to remove waste and toxins, keeping our minds sharp and healthy. This complex process is known as the glymphatic system, first described by pioneering neuroscientist Maiken Nedergaard in 2012.

However, despite its significance, scientists still have much to learn about how this system functions. A crucial aspect of understanding the glymphatic system is determining how quickly the fluid that helps remove waste moves through the brain. Measuring this slow circulation has proven to be a significant challenge, as researchers need methods that can observe the process without causing permanent damage.

The Challenge of Measuring Brain Fluid Flow

Professor Douglas Kelley from the University of Rochester’s Department of Mechanical Engineering explains, ‘You can put a microscope on a small patch of the brain and watch what’s happening there with a lot of detail, but it’s only a tiny view of the overall process.’ To overcome this limitation, Kelley and his team used artificial intelligence to develop a physics-informed AI approach for calculating fluid flow speeds from magnetic resonance imaging (MRI) data.

In a groundbreaking study published in Science Advances, the researchers describe how they trained neural networks using videos that showed dye spreading through brain tissue over time. By analyzing how the dye moved, the AI could estimate both the speed of the fluid and the permeability of the surrounding brain tissue.

Two Very Different Speeds Inside the Brain

The findings revealed two major routes by which the glymphatic system removes particles from the brain, including amyloid beta proteins associated with Alzheimer’s disease. The speeds of those routes are dramatically different, with the fluid moving at a few microns per second in more open areas and about 50 times slower deeper inside brain tissue.

The team is currently using animals such as mice to establish baseline measurements of how fluid normally moves through the brain. These measurements are helping researchers develop and improve the AI tools, which could eventually be used to compare circulation patterns between healthy and diseased brains, as well as between younger and older brains.

Ultimately, the researchers hope to extend their approach to humans, enabling them to measure fluid circulation in and around the brain. This could lead to new ways of studying neurological disease and brain injury.

‘We’re working hard toward being able to measure the flow of water-like fluids in and around human brains because then the clinical applications get a lot more important and exciting,’ says Kelley.