BACKGROUND: 22q11.2 Deletion Syndrome (22q11DS) is a genetic, neurodevelopmental disorder characterized by a chromosomal deletion and a distinct cognitive profile. Although abnormalities in the macrostructure of the cortex have been identified in individuals with 22q11DS, it is not known if there are additional microstructural changes in gray matter regions in this syndrome, and/or if such microstructural changes are associated with cognitive functioning.
METHODS: This study employed a novel diffusion MRI measure, the Heterogeneity of Fractional Anisotropy (HFA), to examine variability in the microstructural organization of the cortex in healthy young adults (N = 30) and those with 22q11DS (N = 56). Diffusion MRI, structural MRI, clinical and cognitive data were acquired.
RESULTS: Compared to controls, individuals with 22q11DS evinced increased HFA in cortical association (p = .003, d = 0.86) and paralimbic (p < .0001, d = 1.2) brain areas, whereas no significant differences were found between the two groups in primary cortical brain areas. Additionally, increased HFA of the right paralimbic area was associated with poorer performance on tests of response inhibition, i.e., the Stroop Test (rho = -0.37 p = .005) and the Gordon Diagnostic System Vigilance Commission (rho = -0.41 p = .002) in the 22q11DS group. No significant correlations were found between HFA and cognitive abilities in the healthy control group.
CONCLUSIONS: These findings suggest that cortical microstructural disorganization may be a neural correlate of response inhibition in individuals with 22q11DS. Given that the migration pattern of neural crest cells is disrupted at the time of early brain development in 22q11DS, we hypothesize that these neural alterations may be neurodevelopmental in origin, and reflect cortical dysfunction associated with cognitive deficits.
Microstructure imaging techniques based on tensor-valued diffusion encoding have gained popularity within the MRI research community. Unlike conventional diffusion encoding-applied along a single direction in each shot-tensor-valued encoding employs diffusion encoding along multiple directions within a single preparation of the signal. The benefit is that such encoding may probe tissue features that are not accessible by conventional encoding. For example, diffusional variance decomposition (DIVIDE) takes advantage of tensor-valued encoding to probe microscopic diffusion anisotropy independent of orientation coherence. The drawback is that tensor-valued encoding generally requires gradient waveforms that are more demanding on hardware; it has therefore been used primarily in MRI systems with relatively high performance. The purpose of this work was to explore tensor-valued diffusion encoding on clinical MRI systems with varying performance to test its technical feasibility within the context of DIVIDE. We performed whole-brain imaging with linear and spherical b-tensor encoding at field strengths between 1.5 and 7 T, and at maximal gradient amplitudes between 45 and 80 mT/m. Asymmetric gradient waveforms were optimized numerically to yield b-values up to 2 ms/μm2. Technical feasibility was assessed in terms of the repeatability, SNR, and quality of DIVIDE parameter maps. Variable system performance resulted in echo times between 83 to 115 ms and total acquisition times of 6 to 9 minutes when using 80 signal samples and resolution 2×2×4 mm3. As expected, the repeatability, signal-to-noise ratio and parameter map quality depended on hardware performance. We conclude that tensor-valued encoding is feasible for a wide range of MRI systems-even at 1.5 T with maximal gradient waveform amplitudes of 33 mT/m-and baseline experimental design and quality parameters for all included configurations. This demonstrates that tissue features, beyond those accessible by conventional diffusion encoding, can be explored on a wide range of MRI systems.
Instead of assuming a constant relationship between brain abnormalities and memory impairment, we aimed to examine the stage-dependent contributions of multimodal brain structural and functional deterioration to memory impairment in the Alzheimer's disease (AD) continuum. We assessed grey matter volume, white matter (WM) microstructural measures (free-water (FW) and FW-corrected fractional anisotropy), and functional connectivity of the default mode network (DMN) in 54 amnestic mild cognitive impairment (aMCI) and 46 AD. We employed a novel sparse varying coefficient model to investigate how the associations between abnormal brain measures and memory impairment varied throughout disease continuum. We found lower functional connectivity in the DMN was related to worse memory across AD continuum. Higher widespread white matter FW and lower fractional anisotropy in the fornix showed a stronger association with memory impairment in the early aMCI stage; such WM-memory associations then decreased with increased dementia severity. Notably, the effect of the DMN atrophy occurred in early aMCI stage, while the effect of the medial temporal atrophy occurred in the AD stage. Our study provided evidence to support the hypothetical progression models underlying memory dysfunction in AD cascade and underscored the importance of FW increases and DMN degeneration in early stage of memory deficit.
Diffusion-attenuated MR signal for heterogeneous media has been represented as a sum of signals from anisotropic Gaussian sub-domains to the extent that this approximation is permissible. Any effect of macroscopic (global or ensemble) anisotropy in the signal can be removed by averaging the signal values obtained by differently oriented experimental schemes. The resulting average signal is identical to what one would get if the micro-domains are isotropically (e.g., randomly) distributed with respect to orientation, which is the case for "powdered" specimens. We provide exact expressions for the orientationally-averaged signal obtained via general gradient waveforms when the microdomains are characterized by a general diffusion tensor possibly featuring three distinct eigenvalues. This extends earlier results which covered only axisymmetric diffusion as well as measurement tensors. Our results are expected to be useful in not only multidimensional diffusion MR but also solid-state NMR spectroscopy due to the mathematical similarities in the two fields.
Alterations in parietal and temporal white matter microstructure derived from diffusion tensor imaging occur in preclinical and clinical Alzheimer's disease. Amyloid beta (Aβ) deposition and such white matter alterations are two pathological hallmarks of Alzheimer's disease. However, the relationship between these pathologies is not yet understood, partly since conventional diffusion MRI methods cannot distinguish between cellular and extracellular processes. Thus, we studied Aβ-associated longitudinal diffusion MRI changes in Aβ-positive (N = 21) and Aβ-negative (N = 51) cognitively normal elderly obtained from the Alzheimer's Disease Neuroimaging Initiative dataset using linear mixed models. Aβ-positivity was based on Alzheimer's Disease Neuroimaging Initiative amyloid-PET recommendations using a standardized uptake value ratio cut-off of 1.11. We used free-water imaging to distinguish cellular and extracellular changes. We found that Aβ-positive subjects had increased baseline right uncinate fasciculus free-water fraction (FW), associated with worse baseline Alzheimer's disease assessment scale scores. Furthermore, Aβ-positive subjects showed faster decrease in fractional anisotropy (FW-corrected) in the right uncinate fasciculus and faster age-dependent right inferior longitudinal fasciculus FW increases over time. Right inferior longitudinal fasciculus FW increases were associated with greater memory decline. Importantly, these results remained significant after controlling for gray and white matter volume and hippocampal volume. This is the first study to illustrate the influence of Aβ burden on early longitudinal (in addition to baseline) white matter changes in cognitively normal elderly individuals at-risk of Alzheimer's disease, thus underscoring the importance of longitudinal studies in assessing microstructural alterations in individuals at risk of Alzheimer's disease prior to symptoms onset.
BACKGROUND: Cor pulmonale (right ventricular dilation) and cor pulmonale parvus (right ventricular shrinkage) are both described in chronic obstructive pulmonary disease (COPD). The identification of emphysema as a shared risk factor suggests that additional disease characterization is needed to understand these widely divergent cardiac processes. Here, we explored the relationship between CT measures of emphysema and distal pulmonary arterial morphology with RV volume, as well as their association with exercise capacity and mortality in ever-smokers with COPD enrolled in the COPDGene Study.
METHODS: Epicardial (myocardium and chamber) RV volume (RVEV), distal pulmonary arterial blood vessel volume (arterial BV5: vessels <5mm2 in cross section) as well as objective measures of emphysema were extracted from 3,506 COPDGene CT scans. Multivariable linear and Cox regression models as well as the log rank test were used to explore the association between emphysema, arterial BV5 and RVEV with exercise capacity (6-MWD) and all-cause mortality.
RESULTS: The RVEV was approximately 10% smaller in GOLD 4 vs GOLD 1 COPD (P<0.0001). In multivariable modeling, a 10mL decrease in arterial BV5 (pruning) was associated with a 1mL increase in RVEV. For a given amount of emphysema, relative preservation of the arterial BV5 was associated with a smaller RVEV. An increased RVEV was associated with reduced 6-MWD and in those with arterial pruning an increased mortality.
CONCLUSIONS: Pulmonary arterial pruning is associated with clinically significant increases in right ventricular volume in smokers with COPD and is related to exercise capacity and mortality in COPD.
Alterations in cognitive performance have been noted in nondemented subjects with elevated accumulation of amyloid-β (Aβ) fibrils. However, it is not yet understood whether brain function is already influenced by Aβ deposition during the very earliest stages of the disease. We therefore investigated associations between [18F]Flutemetamol PET, resting-state functional connectivity, gray and white matter structure and cognitive performance in 133 cognitively normal elderly that exhibited normal global Aβ PET levels. [18F]Flutemetamol uptake in regions known to accumulate Aβ fibrils early in preclinical AD (i.e., mainly certain parts of the default-mode network) was positively associated with dynamic but not static functional connectivity (r = 0.77). Dynamic functional connectivity was further related to better cognitive performance (r = 0.21-0.72). No significant associations were found for Aβ uptake with gray matter volume or white matter diffusivity. The findings demonstrate that the earliest accumulation of Aβ fibrils is associated with increased functional connectivity, which occurs before any structural alterations. The enhanced functional connectivity may reflect a compensatory mechanism to maintain high cognitive performance in the presence of increasing amyloid accumulation during the earliest phases of AD.
RATIONALE: Cigarette smoke exposure is a risk factor for many lung diseases, and histologic studies suggest tobacco-related vasoconstriction and vessel loss plays a role in the development of emphysema. However, it remains unclear how tobacco affects the pulmonary vasculature in general populations with a typical range of tobacco exposure, and whether these changes are detectable by radiographic methods.
OBJECTIVE: To determine whether tobacco exposure in a generally healthy population manifests as lower pulmonary blood vessel volumes and vascular pruning on imaging.
METHODS: 2,410 Framingham Heart Study participants with demographic data and smoking history underwent volumetric whole-lung computed tomography (CT) from 2008-2011. Automated algorithms calculated the total volume of all intrapulmonary vessels (TBV), smaller peripheral vessels (BV5), and the relative fraction of small vessels (BV5/TBV). Tobacco exposure was assessed as smoking status, cumulative pack-years, and second-hand exposure. We constructed multivariable linear regression models to evaluate associations of cigarette exposure and pulmonary blood vessel volume measures, adjusting for demographic covariates including age, sex, height, weight, education, occupation, and median neighborhood income.
RESULTS: All metrics of tobacco exposure (including smoking status, pack-years, and second-hand exposure) were consistently associated with higher absolute pulmonary blood vessel volume, higher small vessel volume, and/or higher small vessel fraction. For example, ever-smokers had a 4.6mL higher TBV (95% CI: 2.9-6.3, p<0.0001), 2.1mL higher BV5 (95% CI: 1.3-2.9, p<0.0001), and 0.28 percentage-point higher BV5/TBV (95% CI: 0.03-0.52, p=0.03) compared to never-smokers. These associations remained significant after adjustment for percent-predicted FEV, cardiovascular comorbidities, and did not differ based on presence or absence of airflow obstruction.
CONCLUSIONS: Using CT imaging, we found that cigarette exposure was associated with higher pulmonary blood vessel volumes, especially in the smaller peripheral vessels. While histologically, tobacco-related vasculopathy is characterized by vessel narrowing and loss, our results suggest that radiographic vascular pruning may not be a surrogate of these pathologic changes.
Time constraints placed on magnetic resonance imaging often restrict the application of advanced diffusion MRI (dMRI) protocols in clinical practice and in high throughput research studies. Therefore, acquisition strategies for accelerated dMRI have been investigated to allow for the collection of versatile and high quality imaging data, even if stringent scan time limits are imposed. Diffusion spectrum imaging (DSI), an advanced acquisition strategy that allows for a high resolution of intra-voxel microstructure, can be sufficiently accelerated by means of compressed sensing (CS) theory. CS theory describes a framework for the efficient collection of fewer samples of a data set than conventionally required followed by robust reconstruction to recover the full data set from sparse measurements. For an accurate recovery of DSI data, a suitable acquisition scheme for sparse q-space sampling and the sensing and sparsifying bases for CS reconstruction need to be selected. In this work we explore three different types of q-space undersampling schemes and two frameworks for CS reconstruction based on either Fourier or SHORE basis functions. After CS recovery, diffusion and microstructural parameters and orientational information are estimated from the reconstructed data by means of state-of-the-art processing techniques for dMRI analysis. By means of simulation, diffusion phantom and in vivo DSI data, an isotropic distribution of q-space samples was found to be optimal for sparse DSI. The CS reconstruction results indicate superior performance of Fourier-based CS-DSI compared to the SHORE-based approach. Based on these findings we outline an experimental design for accelerated DSI and robust CS reconstruction of the sparse measurements that is suitable for the application within time-limited studies.
Aptitude for and proficiency in acquiring new languages varies in the human population but their neural bases are largely unknown. We investigated the influence of cortical thickness on language learning predictors measured by the LLAMA tests and a pitch-change discrimination test. The LLAMA tests are first language-independent assessments of language learning aptitude for vocabulary, phonetic working memory, sound-symbol correspondence (not used in this study), and grammatical inferencing. Pitch perception proficiency is known to predict aptitude for learning new phonology. Results show a correlation between scores in a grammatical meaning-inferencing aptitude test and cortical thickness of Broca's area (r(30) = 0.65, p = 0.0202) and other frontal areas (r(30) = 0.66, p = 0.0137). Further, a correlation was found between proficiency in discriminating pitch-change direction and cortical thickness of the right Broca homologue (r(30) = 0.57, p = 0.0006). However, no correlations were found for aptitude for vocabulary learning or phonetic working memory. Results contribute to locating cortical regions important for language-learning aptitude.
INTRODUCTION: Abnormalities in the corpus callosum (CC) and the lateral ventricles (LV) are hallmark features of schizophrenia. These abnormalities have been reported in chronic and in first episode schizophrenia (FESZ). Here we explore further associations between CC and LV in FESZ using diffusion tensor imaging (DTI).
METHODS: . Sixteen FESZ patients and 16 healthy controls (HC), matched on age, gender, and handedness participated in the study. Diffusion and structural imaging scans were acquired on a 3T GE Signa magnet. Volumetric measures for LV and DTI measures for five CC subdivisions were completed in both groups. In addition, two-tensor tractography, the latter corrected for free-water (FA), was completed for CC. Correlations between LV and DTI measures of the CC were examined in both groups, while correlations between DTI and clinical measures were examined in only FESZ.
RESULTS: Results from two-tensor tractography demonstrated decreased FA and increased trace and radial diffusivity (RD) in the five CC subdivisions in FESZ compared to HC. Central CC diffusion measures in FESZ were significantly correlated with volume of the LV, i.e., decreased FA values were associated with larger LV volume, while increased RD and trace values were associated with larger LV volume. In controls, correlations were also significant, but they were in the opposite direction from FESZ. In addition, decreased FA in FESZ was associated with more positive symptoms.
DISCUSSION: Partial volume corrected FA, RD, and trace abnormalities in the CC in FESZ suggest possible de- or dys-myelination, or changes in axonal diameters, all compatible with neurodevelopmental theories of schizophrenia. Correlational findings between the volume of LV and diffusion measures in FESZ reinforce the concept of a link between abnormalities in the LV and CC in early stages of schizophrenia and are also compatible with neurodevelopmental abnormalities in this population.
Conventional diffusion MRI yields voxel-averaged parameters that suffer from ambiguities for heterogeneous anisotropic materials such as brain tissue. Using principles from solid-state NMR spectroscopy, we have previously introduced the shape of the diffusion encoding tensor as a separate acquisition dimension that disentangles isotropic and anisotropic contributions to the observed diffusivities, thereby allowing for unconstrained data inversion into diffusion tensor distributions with "size," "shape," and orientation dimensions. Here we combine our recent non-parametric data inversion algorithm and data acquisition protocol with an imaging pulse sequence to demonstrate spatial mapping of diffusion tensor distributions using a previously developed composite phantom with multiple isotropic and anisotropic components. We propose a compact format for visualizing two-dimensional arrays of the distributions, new scalar parameters quantifying intra-voxel heterogeneity, and a binning procedure giving maps of all relevant parameters for each of the components resolved in the multidimensional distribution space.
Lung vessel segmentation has been widely explored by the biomedical image processing community; however, the differentiation of arterial from venous irrigation is still a challenge. Pulmonary artery-vein (AV) segmentation using computed tomography (CT) is growing in importance owing to its undeniable utility in multiple cardiopulmonary pathological states, especially those implying vascular remodelling, allowing the study of both flow systems separately. We present a new framework to approach the separation of tree-like structures using local information and a specifically designed graph-cut methodology that ensures connectivity as well as the spatial and directional consistency of the derived subtrees. This framework has been applied to the pulmonary AV classification using a random forest (RF) pre-classifier to exploit the local anatomical differences of arteries and veins. The evaluation of the system was performed using 192 bronchopulmonary segment phantoms, 48 anthropomorphic pulmonary CT phantoms, and 26 lungs from noncontrast CT images with precise voxel-based reference standards obtained by manually labelling the vessel trees. The experiments reveal a relevant improvement in the accuracy ( ∼ 20%) of the vessel particle classification with the proposed framework with respect to using only the pre-classification based on local information applied to the whole area of the lung under study. The results demonstrated the accurate differentiation between arteries and veins in both clinical and synthetic cases, specifically when the image quality can guarantee a good airway segmentation, which opens a huge range of possibilities in the clinical study of cardiopulmonary diseases.
It has been previously reported that hepatitis B e‑antigen (HBeAg) induces microRNA (miR)‑155 expression and promotes liver injury by increasing inflammatory cytokine production in macrophages. Moreover, it was previously demonstrated that miR‑210 alleviates lipopolysaccharide‑stimulated proinflammatory cytokine production in macrophages. In addition, accumulating evidence suggests that miR‑210 is able to suppress hepatitis B virus (HBV) replication in HepG2.2.15 cells. However, it remains unclear whether miR‑210, similar to miR‑155, affects the progress of hepatitis B by regulating macrophage function. Reverse transcription‑quantitative polymerase chain reaction analysis was used to detect miR‑210 levels in serum and cells. HBV‑associated antigens stimulated different types of macrophages and facilitated the observation of the effects of these antigens on miR‑210 expression in macrophages. Co‑culture of peripheral blood monocytes from healthy controls and the serum of patients with chronic hepatitis B (CHB) was conducted to evaluate the effect of HBV‑associated elements in the serum on the expression of the macrophage miR‑210 in vivo. It was observed that miR‑210 expression levels were decreased in the peripheral blood monocytes (PBMs) and serum of patients with CHB and negatively associated with serum alanine aminotransferase and aspartate aminotransferase, but not other clinical parameters including hepatitis B surface antigen (HBsAg), HBeAg, anti‑HBe antibody (HBeAb) and hepatitis B core antibody (HBcAb) and HBV‑DNA. Notably, it was demonstrated that miR‑210 expression was not affected by treatment with HBV‑associated antigens in different types of macrophages. Notably, the serum of patients with CHB was able to markedly downregulate the miR‑210 expression of PBMs in healthy controls. These findings suggested that, unlike the induction of miR‑155 by HBeAg, there may be certain other elements, apart from HBV‑associated antigens, regulating miR‑210 levels in the serum and PBMs of patients with CHB that affect macrophage activation.
Research on age-related memory alterations traditionally targets individuals aged ≥65 years. However, recent studies emphasize the importance of early aging processes. We therefore aimed to characterize variation in brain gray matter structure in early midlife as a function of sex and menopausal status. Subjects included 94 women (33 premenopausal, 29 perimenopausal, and 32 postmenopausal) and 99 demographically comparable men from the New England Family Study. Subjects were scanned with a high-resolution T1 sequence on a 3 T whole body scanner. Sex and reproductive-dependent structural differences were evaluated using Box's M test and analysis of covariances (ANCOVAs) for gray matter volumes. Brain regions of interest included dorsolateral prefrontal cortex (DLPFC), inferior parietal lobule (iPAR), anterior cingulate cortex (ACC), hippocampus (HIPP), and parahippocampus. While we observed expected significant sex differences in volume of hippocampus with women of all groups having higher volumes than men relative to cerebrum size, we also found significant differences in the covariance matrices of perimenopausal women compared with postmenopausal women. Associations between ACC and HIPP/iPAR/DLPFC were higher in postmenopausal women and correlated with better memory performance. Findings in this study underscore the importance of sex and reproductive status in early midlife for understanding memory function with aging.
The corticospinal tract (CST) is one of the most well studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many notable traumatic conditions and diseases such as stroke, spinal cord injury (SCI) or amyotrophic lateral sclerosis (ALS). With the advent of diffusion MRI and tractography the computational representation of the human CST in a 3D model became available. However, the representation of the entire CST and, specifically, the hand motor area has remained elusive. In this paper we propose a novel method, using manually drawn ROIs based on robustly identifiable neuroanatomic structures to delineate the entire CST and isolate its hand motor representation as well as to estimate their variability and generate a database of their volume, length and biophysical parameters. Using 37 healthy human subjects we performed a qualitative and quantitative analysis of the CST and the hand-related motor fiber tracts (HMFTs). Finally, we have created variability heat maps from 37 subjects for both the aforementioned tracts, which could be utilized as a reference for future studies with clinical focus to explore neuropathology in both trauma and disease states.
BACKGROUND: Brainstem-focused mechanisms supporting transcutaneous auricular VNS (taVNS) effects are not well understood, particularly in humans. We employed ultrahigh field (7T) fMRI and evaluated the influence of respiratory phase for optimal targeting, applying our respiratory-gated auricular vagal afferent nerve stimulation (RAVANS) technique.
HYPOTHESIS: We proposed that targeting of nucleus tractus solitarii (NTS) and cardiovagal modulation in response to taVNS stimuli would be enhanced when stimulation is delivered during a more receptive state, i.e. exhalation.
METHODS: Brainstem fMRI response to auricular taVNS (cymba conchae) was assessed for stimulation delivered during exhalation (eRAVANS) or inhalation (iRAVANS), while exhalation-gated stimulation over the greater auricular nerve (GANctrl, i.e. earlobe) was included as control. Furthermore, we evaluated cardiovagal response to stimulation by calculating instantaneous HF-HRV from cardiac data recorded during fMRI.
RESULTS: Our findings demonstrated that eRAVANS evoked fMRI signal increase in ipsilateral pontomedullary junction in a cluster including purported NTS. Brainstem response to GANctrl localized a partially-overlapping cluster, more ventrolateral, consistent with spinal trigeminal nucleus. A region-of-interest analysis also found eRAVANS activation in monoaminergic source nuclei including locus coeruleus (LC, noradrenergic) and both dorsal and median raphe (serotonergic) nuclei. Response to eRAVANS was significantly greater than iRAVANS for all nuclei, and greater than GANctrl in LC and raphe nuclei. Furthermore, eRAVANS, but not iRAVANS, enhanced cardiovagal modulation, confirming enhanced eRAVANS response on both central and peripheral neurophysiological levels.
CONCLUSION: 7T fMRI localized brainstem response to taVNS, linked such response with autonomic outflow, and demonstrated that taVNS applied during exhalation enhanced NTS targeting.
Progress in neurodevelopmental brain research has been achieved through the use of animal models. Such models not only help understanding biological changes that govern brain development, maturation and aging, but are also essential for identifying possible mechanisms of neurodevelopmental and age-related chronic disorders, and to evaluate possible interventions with potential relevance to human disease. Genetic relationship of rhesus monkeys to humans makes those animals a great candidate for such models. With the typical lifespan of 25 years, they undergo cognitive maturation and aging that is similar to this observed in humans. Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking white matter brain maturation and aging. While lifespan trajectories of white matter changes have been mapped in humans, such knowledge is not available for nonhuman primates. Here, we analyze and model lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys. We report quantitative parameters (including slopes and peaks) of lifespan trajectories for 8 individual white matter tracts. We show different trajectories for cellular and extracellular microstructural imaging components that are associated with white matter maturation and aging, and discuss similarities and differences between those in humans and rhesus monkeys, the importance of our findings, and future directions for the field. Significance Statement: Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking brain maturation and aging. While lifespan trajectories of structural white matter changes have been mapped in humans, such knowledge is not available for rhesus monkeys. We present here results of the analysis and modeling of the lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys (age 4-27). We report and anatomically map lifespan changes related to cellular and extracellular microstructural components that are associated with white matter maturation and aging.