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Diffusion MRI is a powerful tool for imaging brain structure, but it is challenging to discern the biological underpinnings of plasticity inferred from these and other non-invasive MR measurements. Biophysical modeling of the diffusion signal aims to render a more biologically rich image of tissue microstructure, but the application of these models comes with important caveats. A separate approach for gaining biological specificity has been to seek converging evidence from multi-modal datasets. Here we use metrics derived from diffusion kurtosis imaging (DKI) and the white matter tract integrity (WMTI) model along with quantitative MRI measurements of T1 relaxation to characterize changes throughout the white matter during an 8-week, intensive reading intervention (160 total hours of instruction). Behavioral measures, multi-shell diffusion MRI data, and quantitative T1 data were collected at regular intervals during the intervention in a group of 33 children with reading difficulties (7-12 years old), and over the same period in an age-matched non-intervention control group. Throughout the white matter, mean ‘extra-axonal’ diffusivity was inversely related to intervention time. In contrast, model estimated axonal water fraction (AWF), overall diffusion kurtosis, and T1 relaxation time showed no significant change over the intervention period. Both diffusion and quantitative T1 based metrics were correlated with pre-intervention reading performance, albeit with distinct anatomical distributions. These results are consistent with the view that rapid changes in diffusion properties reflect phenomena other than widespread changes in myelin density. We discuss this result in light of recent work highlighting non-axonal factors in experience-dependent plasticity and learning.HighlightsDiffusion MRI measurements in white matter show changes linked to an educational intervention.Tissue modeling results point to changes within the extra-axonal space.Complementary MRI measurements fail to suggest a widespread change in white matter in myelination over the intervention period.Both diffusion and quantitative T1 measures correlate with pre-intervention reading skill.

Diffusion MRI tractography is essential for reconstructing white-matter projections in the living human brain. Yet tractography results miss some projections and falsely identify others. A challenging example is the optic radiation (OR) that connects the thalamus and the primary visual cortex. Here, we tested whether OR tractography can be optimized using quantitative T1 mapping. Based on histology, we proposed that myelin-sensitive T1 values along the OR should remain consistently low compared with adjacent white matter. We found that complementary information from the T1 map allows for increasing the specificity of the reconstructed OR tract by eliminating falsely identified projections. This T1-filtering outperforms other, diffusion-based tractography filters. These results provide evidence that the smooth microstructural signature along the tract can be used as constructive input for tractography. Finally, we demonstrate that this approach can be applied in a case of multiple sclerosis, and generalized to the HCP-available MRI measurements. We conclude that multimodal MRI microstructural information can be used to eliminate spurious tractography results in the case of the OR.

Reading-related responses in the lateral ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are acquired during childhood. Here, we tested the hypothesis that white matter fascicles and gray matter microstructure predict the location of reading-related responses in lateral VTC. We obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in adding and color tasks; dMRI was used to identify the brain’s fascicles and to map their endpoints density in lateral VTC; qMRI was used to measure proton relaxation time (T1), which depends on cortical tissue microstructure. We fit linear models that predict reading-related responses in lateral VTC from endpoint density and T1 and used leave-one-subject-out cross-validation to assess prediction accuracy. Using a subset of our participants (N=10, feature selection set), we find that i) endpoint density of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) are significant predictors of reading-related responses, and ii) cortical T1 of lateral VTC further improves the predictions of the fascicle model. Next, in the remaining 20 participants (validation set), we showed that a linear model that includes T1, AF, ILF and VOF significantly predicts i) the map of reading-related responses across lateral VTC and ii) the location of the visual word form area, a region critical for reading. Overall, our data-driven approach reveals that the AF, ILF, VOF and cortical microstructure have a consistent spatial relationship with an individual’s reading-related responses in lateral VTC.HighlightsThe ILF, AF, and VOF predict the spatial layout of reading-related responses in VTCGray matter microstructure improves the prediction of reading-related responsesFascicles and gray matter structure together predict the location of the VWFA

Recent years have seen a growing interest in relating MRI measurements to the structural-biophysical properties of white matter fibers. The fiber g-ratio, defined as the ratio between the inner and outer radii of the axon myelin sheath, is an important structural property of white matter, affecting signal conduction. Recently proposed modeling methods that use a combination of quantitative-MRI signals, enable a measurement of the fiber g-ratio in vivo. Here we use an MRI-based g-ratio estimation to observe the variance of the g-ratio within the corpus callosum, and evaluate sex and age related differences. To estimate the g-ratio we used a model ( Stikov et al., 2011 ; Duval et al., 2017 ) based on two different WM microstructure parameters: the relative amounts of myelin (myelin volume fraction, MVF) and fibers (fiber volume fraction, FVF) in a voxel. We derived the FVF from the fractional anisotropy (FA), and estimated the MVF by using the lipid and macromolecular tissue volume (MTV), calculated from the proton density (Mezer et al., 2013). In comparison to other methods of estimating the MVF, MTV represents a stable parameter with a straightforward route of acquisition. To establish our model, we first compared histological MVF measurements (West et al., 2016) with the MRI derived MTV. We then implemented our model on a large database of 92 subjects (44 males), aged 7 to 81, in order to evaluate age and sex related changes within the corpus callosum. Our results show that the MTV provides a good estimation of MVF for calculating g-ratio, and produced values from the corpus callosum that correspond to those found in animals ex vivo and are close to the theoretical optimum, as well as to published in vivo data. Our results demonstrate that the MTV derived g-ratio provides a simple and reliable in vivo g-ratio-weighted (GR*) measurement in humans. In agreement with theoretical predictions, and unlike other tissue parameters measured with MRI, the g-ratio estimations were found to be relatively stable with age, and we found no support for a significant sexual dimorphism with age.

article i nfo Article history: Accepted 14 November 2013 Available online 21 November 2013 Brain development occurs rapidly during the first few years of life involving region-specific changes in both gray matter and white matter. Due to the inherent difficulties in acquiring magnetic resonance imaging data in young children,littleisknownaboutthepropertiesofwhite matterintypicallydeveloping toddlers.Inthecontextofan ongoing study of young children with autism spectrum disorder, we collected diffusion-weighted imaging data during natural nocturnal sleep in a sample of young (mean age = 35 months) typically developing male and female (n = 41 and 25, respectively) children. Axial diffusivity, radial diffusivity, mean diffusivity and fractional anisotropy were measured at 99 points along the length of 18 major brain tracts. Influences of hemisphere, age, sex, and handedness were examined. We find that diffusion properties vary signifi- cantly along the length of the majority of tracks. We also identify hemispheric and sex differences in diffu- sion properties in several tracts. Finally, we find the relationship between age and diffusion parameters changes along the tract length illustrating variability in age-related white-matter development at the tract level.