Life span maturation and degeneration of human brain white matter

Properties of human brain tissue change across the lifespan. Modeling of white matter age changes measured with quantitative MRI shows that maturation reaches a peak at around age 40, and then begins to unravel. By the end of life, our brain’s fat levels return to about where they were at age 7. The time-courses of different MRI markers demonstrate that multiple biological processes drive changes in white-matter tissue properties over the lifespan.

HFSP Long-Term Fellow Aviv Mezer and colleagues
authored on Fri, 19 September 2014

White matter plays a critical role in brain development and decline. Several diseases including schizophrenia and autism are associated with white matter abnormalities. Despite its importance in normal development and disease, no metric exists for determining whether any person’s white matter falls within a normal range, particularly if the people were scanned using different machines.

Newly developed quantitative MRI techniques (published recently: Mezer and colleagues, Nature Medicine, 2013) enable a normal curve for white matter levels throughout life to be developed. In a follow-up work, Yeatman, Wandell and Mezer (Nature communications, 2014), imaging of 24 regions within the brains of 102 people aged seven to 85 enabled the establishment of a set of curves showing the increase and then eventual decrease in white matter in each of the 24 regions throughout life. The normal curve for brain composition was found to have a rainbow-shape. It starts and ends with roughly the same amount of white matter and peaks between ages 30 to 50. However, each of the 24 regions changes to a different degree. Some parts of the brain like those that control movement are long, flat arcs, staying relatively stable throughout life. Others, like the areas involved in thinking and learning are steep arches, maturing dramatically and then falling off quickly.

Figure: Each white matter fascicle is colored based on the amount of change in R1 (R1 at peak minus R1 at age 8) over the lifespan (cross sectional); blue corresponds to less change and red to more change.

The work combines multiple quantitative MRI measurements (R1 relaxation rate, macromolecular tissue volume and diffusivity) to model white matter development and aging over an 80-year period of the lifespan. Developmental processes create new tissue that displaces water, leading to higher R1 relaxation rates, volume measurements and lower diffusivity within the white matter.  Some MRI parameters’ decline with aging is mirror-symmetric with the increase during development, while other show asymmetric shapes. These results suggest that even though tissue is lost during aging, the elderly brain does not revert back to the biology of a child’s brain. There are multiple active lifespan processes and not all of them are symmetric. This observation is supported by histology in aging macaques, showing that axons and myelin are lost but the continued creation of new astrocytes, microglia and oligodendrocytes fill the empty space.

Lastly, in this paper, Aviv Mezer and his collaborators showed that they could identify people with MS as being off the normal curve throughout regions of the brain, including places where there are no visible lesions. This could provide an alternative method to monitor and diagnose MS.

Combining multiple measurement modalities makes it possible to dissociate multiple biological processes that progress independently over the lifespan. Models of the processes underlying healthy white matter maturation will offer new insight into the coupling between biological and cognitive development and allow white matter abnormalities to be rapidly diagnosed and monitored.


Lifespan maturation and degeneration of human brain white matter.Yeatman, J. D., Wandell, B. A., & Mezer, A. A. (2014).  Nat Commun, 5. 2014.

Other references

Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging. Mezer, A., Yeatman, J. D., Stikov, N., Kay, K. N., Cho, N.-J., Dougherty, R. F., Perry, P.M., Parvizi, J., Hua, H. L., Butts-Paully, K., Wandell, B. a. (2013).  Nature Medicine, 19(12), 1667–72. doi:10.1038/nm.3390

Link to abstract and/or article

Pubmed link