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Lifespan maturation and degeneration of human brain white matter.

Yeatman JD, Wandell BA, Mezer AA - Nat Commun (2014)

Bottom Line: Quantitative measurements of macromolecule tissue volume (MTV) confirm that R1 is an accurate index of the growth of new brain tissue.In contrast to R1, diffusion development follows an asymmetric time-course with rapid childhood changes but a slow rate of decline in old age.Together, the time-courses of R1 and diffusion changes demonstrate that multiple biological processes drive changes in white-matter tissue properties over the lifespan.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Psychology, Stanford University, Jordan Hall, 450 Serra Mall, Stanford, California 94305, USA [2] Stanford University Center for Cognitive and Neurobiological Imaging, Stanford, California 94305, USA.

ABSTRACT
Properties of human brain tissue change across the lifespan. Here we model these changes in the living human brain by combining quantitative magnetic resonance imaging (MRI) measurements of R1 (1/T1) with diffusion MRI and tractography (N=102, ages 7-85). The amount of R1 change during development differs between white-matter fascicles, but in each fascicle the rate of development and decline are mirror-symmetric; the rate of R1 development as the brain approaches maturity predicts the rate of R1 degeneration in aging. Quantitative measurements of macromolecule tissue volume (MTV) confirm that R1 is an accurate index of the growth of new brain tissue. In contrast to R1, diffusion development follows an asymmetric time-course with rapid childhood changes but a slow rate of decline in old age. Together, the time-courses of R1 and diffusion changes demonstrate that multiple biological processes drive changes in white-matter tissue properties over the lifespan.

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R1 maturation and degeneration have symmetric slopes(a) Mean lifespan R1 curve (red) combining the data from all tracts is superiposed on the prediction of the second order polynomial model (black). The mean curve was calculated by fitting a local regression model to the data for all the tracts; the width of the colored line corresponds to the standard error of the model. For R1, there is no systematic difference between the data and the prediction of the symmetric parabola. For every age the model prediction is within 1 standard error of the measurement (diffusivity shown in Supplementary Figure 4). (b) The symmetry of change in R1 over the lifespan can be apreciated by plotting the R1 value in childhood and senescence for each individual tract. The age of peak R1 was calculated and values are plotted at age 10 and at a symmetric number of years past the peak (senescence). In senescence R1 values return to the same level they were in childhood. For diffusivity the values do not return to their childhood level (Supplementary Figure 4b). (c) R1 changes over the lifespan are symmetric for most voxels in the brain. Each particpant’s R1 map was aligned to a custom, R1 template and the voxel R1 value was calculated at age 10 and a symmetric number of years past that voxels peak. The childhood and old-age R1 values are closely matched for each white matter voxel (R2 = 0.70)
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Figure 5: R1 maturation and degeneration have symmetric slopes(a) Mean lifespan R1 curve (red) combining the data from all tracts is superiposed on the prediction of the second order polynomial model (black). The mean curve was calculated by fitting a local regression model to the data for all the tracts; the width of the colored line corresponds to the standard error of the model. For R1, there is no systematic difference between the data and the prediction of the symmetric parabola. For every age the model prediction is within 1 standard error of the measurement (diffusivity shown in Supplementary Figure 4). (b) The symmetry of change in R1 over the lifespan can be apreciated by plotting the R1 value in childhood and senescence for each individual tract. The age of peak R1 was calculated and values are plotted at age 10 and at a symmetric number of years past the peak (senescence). In senescence R1 values return to the same level they were in childhood. For diffusivity the values do not return to their childhood level (Supplementary Figure 4b). (c) R1 changes over the lifespan are symmetric for most voxels in the brain. Each particpant’s R1 map was aligned to a custom, R1 template and the voxel R1 value was calculated at age 10 and a symmetric number of years past that voxels peak. The childhood and old-age R1 values are closely matched for each white matter voxel (R2 = 0.70)

Mentions: We tested the gain-predicts-loss hypothesis by fitting a second order polynomial (parabola) to the lifespan measurements (Figure 5a). The parabola fit the R1 data for each tract as well or better than the more complex models (median R2 = 24%). Each tract matures at the same rate that it declines and a tract’s R1 values are identical when measured at symmetric ages around the peak of the curve (Figure 5bc).


Lifespan maturation and degeneration of human brain white matter.

Yeatman JD, Wandell BA, Mezer AA - Nat Commun (2014)

R1 maturation and degeneration have symmetric slopes(a) Mean lifespan R1 curve (red) combining the data from all tracts is superiposed on the prediction of the second order polynomial model (black). The mean curve was calculated by fitting a local regression model to the data for all the tracts; the width of the colored line corresponds to the standard error of the model. For R1, there is no systematic difference between the data and the prediction of the symmetric parabola. For every age the model prediction is within 1 standard error of the measurement (diffusivity shown in Supplementary Figure 4). (b) The symmetry of change in R1 over the lifespan can be apreciated by plotting the R1 value in childhood and senescence for each individual tract. The age of peak R1 was calculated and values are plotted at age 10 and at a symmetric number of years past the peak (senescence). In senescence R1 values return to the same level they were in childhood. For diffusivity the values do not return to their childhood level (Supplementary Figure 4b). (c) R1 changes over the lifespan are symmetric for most voxels in the brain. Each particpant’s R1 map was aligned to a custom, R1 template and the voxel R1 value was calculated at age 10 and a symmetric number of years past that voxels peak. The childhood and old-age R1 values are closely matched for each white matter voxel (R2 = 0.70)
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4238904&req=5

Figure 5: R1 maturation and degeneration have symmetric slopes(a) Mean lifespan R1 curve (red) combining the data from all tracts is superiposed on the prediction of the second order polynomial model (black). The mean curve was calculated by fitting a local regression model to the data for all the tracts; the width of the colored line corresponds to the standard error of the model. For R1, there is no systematic difference between the data and the prediction of the symmetric parabola. For every age the model prediction is within 1 standard error of the measurement (diffusivity shown in Supplementary Figure 4). (b) The symmetry of change in R1 over the lifespan can be apreciated by plotting the R1 value in childhood and senescence for each individual tract. The age of peak R1 was calculated and values are plotted at age 10 and at a symmetric number of years past the peak (senescence). In senescence R1 values return to the same level they were in childhood. For diffusivity the values do not return to their childhood level (Supplementary Figure 4b). (c) R1 changes over the lifespan are symmetric for most voxels in the brain. Each particpant’s R1 map was aligned to a custom, R1 template and the voxel R1 value was calculated at age 10 and a symmetric number of years past that voxels peak. The childhood and old-age R1 values are closely matched for each white matter voxel (R2 = 0.70)
Mentions: We tested the gain-predicts-loss hypothesis by fitting a second order polynomial (parabola) to the lifespan measurements (Figure 5a). The parabola fit the R1 data for each tract as well or better than the more complex models (median R2 = 24%). Each tract matures at the same rate that it declines and a tract’s R1 values are identical when measured at symmetric ages around the peak of the curve (Figure 5bc).

Bottom Line: Quantitative measurements of macromolecule tissue volume (MTV) confirm that R1 is an accurate index of the growth of new brain tissue.In contrast to R1, diffusion development follows an asymmetric time-course with rapid childhood changes but a slow rate of decline in old age.Together, the time-courses of R1 and diffusion changes demonstrate that multiple biological processes drive changes in white-matter tissue properties over the lifespan.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Psychology, Stanford University, Jordan Hall, 450 Serra Mall, Stanford, California 94305, USA [2] Stanford University Center for Cognitive and Neurobiological Imaging, Stanford, California 94305, USA.

ABSTRACT
Properties of human brain tissue change across the lifespan. Here we model these changes in the living human brain by combining quantitative magnetic resonance imaging (MRI) measurements of R1 (1/T1) with diffusion MRI and tractography (N=102, ages 7-85). The amount of R1 change during development differs between white-matter fascicles, but in each fascicle the rate of development and decline are mirror-symmetric; the rate of R1 development as the brain approaches maturity predicts the rate of R1 degeneration in aging. Quantitative measurements of macromolecule tissue volume (MTV) confirm that R1 is an accurate index of the growth of new brain tissue. In contrast to R1, diffusion development follows an asymmetric time-course with rapid childhood changes but a slow rate of decline in old age. Together, the time-courses of R1 and diffusion changes demonstrate that multiple biological processes drive changes in white-matter tissue properties over the lifespan.

Show MeSH
Related in: MedlinePlus