In this study, we calculated tract covariance to describe the phenomenon of white matter differentiation and de-differentiation across lifespan, using diffusion spectrum imaging (DSI) and whole brain tract-based automatic analysis (TBAA) techniques. Differentiation was found to be highest in the 2nd decade and de-differentiation started to emerge at 3rd decade and peaked at 6th decade.
Subjects: We divided the participants into six groups per decade2 (See Table 1).
Imaging: We acquired data of T1-weighted imaging and DSI on a 3T MRI system (TIM Trio, Siemen) with a 32-channel phased array coil. T1-weighted imaging utilized a MPRAGE pulse sequence: TR/TE = 2000/3 ms, flip angle = 9o, FOV = 256 X 192 X 208mm3, resolution = 1 X 1 X 1 mm3. DSI used a pulsed gradient twice-refocused spin-echo diffusion echo-planar imaging sequence: 102 diffusion-encoding gradients with bmax of 4000 s/mm2, TR/TE = 9600/130 ms, FOV = 200 X 200 mm2, matrix size = 80 X 80, 56 slices, and slice thickness = 2.5 mm.
Analysis: We used TBAA to obtain GFA profiles of 76 white matter tract bundles for each participant3, and mean generalized fractional anisotropy (GFA), fractional anisotropy (FA), and relative anisotropy (RA) values were calculated for each tract. Among the 6 groups, we compared tract covariance which we defined as the partial correlation between each pair of tracts in variations of GFA, FA, RA values across subjects, with age, gender and dropout number of diffusion-weighted images being regressors. For statistics analysis, we used a permutation test to determine whether there were significant differences and describe the differences between group 1 and any other groups as well as the adjacent groups. We disturbed the data of the selected groups and regrouped them randomly. We calculated the new tract covariance and evaluated the difference of the original covariance maps across 2850 pixels. We permutated it for 342000 times and got 342000 tract covariance matrices to obtain 2850 empirical distributions of the differences. We put the difference of the original covariance and found the p value which was defined to be significant if it was located beyond 2 standard deviations. We took the -log of all p values for visualize the difference distribution, the greater the -log│p│, the more dramatic the difference. We overlapped the -log│p│ of the two comparisons groups to show the major trend of the dynamics.
1. Cox, Simon R., et al. "Ageing and brain white matter structure in 3,513 UK Biobank participants." Nature communications 7 (2016): 13629.
2. Westlye, Lars T., et al. "Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry." Cerebral cortex 20.9 (2009): 2055-2068.
3. Chen, Yu‐Jen, et al. "Automatic whole brain tract‐based analysis using predefined tracts in a diffusion spectrum imaging template and an accurate registration strategy." Human brain mapping 36.9 (2015): 3441-3458.
4. Chechik, Gal, Isaac Meilijson, and Eytan Ruppin. "Neuronal regulation: A mechanism for synaptic pruning during brain maturation." Neural computation 11.8 (1999): 2061-2080.