Human Brain White Matter Research Articles

The effects of the serotonin transporter polymorphism and age on frontal white matter integrity in healthy adult women

Studies of populations at genetic risk have the potential to explore the underlying structural and functional mechanisms in the development of psychological disorders. The polymorphic region (5-HTTLPR) in the serotonin transporter gene (SLC6A4) has been associated with major depression (MDD) (Caspi et al., 2003). In healthy women, variation in the human brain white matter microstructure integrity in the uncinate fascicule (UF) has been suggested as an endophenotypes in the development of MDD. Pacheco et al. (2009) found a unique effect of age and 5-HTTLPR within the left frontal UF. The present study examined whether these associations persist along the adult life span. Thirty-seven right-handed healthy women between 21 and 61 years of age were invited for a diffusion MRI study. The functional polymorphism 5-HTTLPR located in the promoter region of the SLC6A4 gene was genotyped using polymerase chain reaction (PCR). Fractional anisotropy (FA) was generated for the UF based on Tract-Based Spatial Statistics (TBSS). Models of emotion regulation circuitry suggest that working memory is important in conscious emotion regulation (Price and Drevets, 2010). To explore if 5-HTTLPR is related to this aspects of emotion processing, a working memory pathway, the superior longitudinal fascicule (SLF) was included. The results demonstrate that age may explain the hypothesized association between 5-HTTLPR and frontal UF white matter integrity in healthy adult women. Both white matter changes associated with the aging process and those associated with growth and development may explain why the earlier reported unique effects of genotype in frontal UF FA do not persist into adulthood.

Brain connectivity and postural control in young traumatic brain injury patients: A diffusion MRI based network analysis

Our previous research on traumatic brain injury (TBI) patients has shown a strong relationship between specific white matter (WM) diffusion properties and motor deficits. The potential impact of TBI-related changes in network organization of the associated WM structural network on motor performance, however, remains largely unknown. Here, we used diffusion tensor imaging (DTI) based fiber tractography to reconstruct the human brain WM networks of 12 TBI and 17 control participants, followed by a graph theoretical analysis. A force platform was used to measure changes in body posture under conditions of compromised proprioceptive and/or visual feedback. Findings revealed that compared with controls, TBI patients showed higher betweenness centrality and normalized path length, and lower values of local efficiency, implying altered network organization. These results were not merely a consequence of differences in number of connections. In particular, TBI patients displayed reduced structural connectivity in frontal, parieto-premotor, visual, subcortical, and temporal areas. In addition, the decreased connectivity degree was significantly associated with poorer balance performance. We conclude that analyzing the structural brain networks with a graph theoretical approach provides new insights into motor control deficits following brain injury.

The magnetic field dependence of water T1 in tissues

The magnetic field dependence of the composite (1)H(2)O nuclear magnetic resonance signal T(1) was measured for excised samples of rat liver, muscle, and kidney over the field range from 0.7 to 7 T (35-300 MHz) with a nuclear magnetic resonance spectrometer using sample-shuttle methods. Based on extensive measurements on simpler component systems, the magnetic field dependence of T(1) of all tissues studied are readily fitted at Larmor frequencies above 1 MHz with a simple relaxation equation consisting of three contributions: a power law, A*ω(-0.60) related to the interaction of water with long-lived-protein binding sites, a logarithmic term B*τ(d) *log(1+1/(ωτ(d))(2)) related to water diffusion at macromolecular interfacial regions, and a constant term associated with the high frequency limit of water-spin-lattice relaxation. The parameters A and B include the concentration and surface area dependences respectively. The logarithmic diffusion term becomes significant at high magnetic fields and is consistent with rapid translational dynamics at macromolecular surfaces. The data are fitted well with translational correlation times of approximately 15 ps for human brain white matter, but with a B value three times larger than gray matter tissues. This analysis suggests that the water-surface translational correlation time is approximately three times longer than in gray matter.

Diffusion time dependence of magnetic resonance diffusion signal decays: an investigation of water exchange in human brain in vivo

To understand the behavior of diffusion signal decays of water in white matter of human brain in vivo and to estimate tissue microstructure parameters such as exchange time of diffusing water molecules in human brain. Diffusion decays were measured over an extended range of diffusion weightings (b-values) up to a maximum of 12,500 s/mm(2) and diffusion times between 19.9 and 53.8 ms in eight healthy human subjects using MRI scans. The diffusion signal decays were all Rician noise corrected and then analyzed using multi-component non-negative least squares (NNLS) data analysis. Three diffusion coefficients including one at (0.930 ± 0.003) × 10(-3) (80 ± 1%) mm(2)/s, another at (0.067 ± 0.002) × 10(-3) (19 ± 1%) mm(2)/s and a small contribution at (1.20 ± 0.02) × 10(-2) (1.00 ± 0.01%) mm(2)/s were observed in the diffusion decay using the highest b-value. The diffusion decays show diffusion time dependence for the slow diffusion coefficient which has not previously been reported. This study presents the accurate diffusion parameters by the use of very large b-values along with Rician noise correction and multi-component data analysis. The experimental results are consistent with the theoretical predictions used to estimate the exchange time of diffusing water molecules for a model of human brain tissue.

Differential development of human brain white matter tracts.

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted ‘U-shape’), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging.

Finsler Streamline Tracking with Single Tensor Orientation Distribution Function for High Angular Resolution Diffusion Imaging

We introduce a new framework based on Riemann-Finsler geometry for the analysis of 3D images with spherical codomain, more precisely, for which each voxel contains a set of directional measurements represented as samples on the unit sphere (antipodal points identified). The application we consider here is in medical imaging, notably in High Angular Resolution Diffusion Imaging (HARDI), but the methods are general and can be applied also in other contexts, such as material science, et cetera, whenever direction dependent quantities are relevant. Finding neural axons in human brain white matter is of significant importance in understanding human neurophysiology, and the possibility to extract them from a HARDI image has a potentially major impact on clinical practice, such as in neuronavigation, deep brain stimulation, et cetera. In this paper we introduce a novel fiber tracking method which is a generalization of the streamline tracking used extensively in Diffusion Tensor Imaging (DTI). This method is capable of finding intersecting fibers in voxels with complex diffusion profiles, and does not involve solving extrema of these profiles. We also introduce a single tensor representation for the orientation distribution function (ODF) to model the probability that a vector corresponds to a tangent of a fiber. The single tensor representation is chosen because it allows a natural choice of Finsler norm as well as regularization via the Laplace-Beltrami operator. In addition we define a new connectivity measure for HARDI-curves to filter the most prominent fiber candidates. We show some very promising results on both synthetic and real data.

Multi-channel Diffusion Tensor Image Registration via adaptive chaotic PSO

Registration or spatial normalization of diffusion tensor images plays an important role in many areas of human brain white matter research, such as analysis of Fraction Anisotropy (FA) or whiter matter tracts. More difficult than registration of scalar images, spatial normalization of tensor images requires two important parts: one is tensor interpolation, and the other is tensor reorientation. Current tensor reorientation strategy possessed many defects during tensor registration. To overcome the shortcomings, we first presented a multi-channel model with one FA and six log-Euclidean tensors, and then proposed an adaptive chaotic particle swarm optimization to find the global minima of the objective function of the multi-channel model. The results on 42 slices inter-subject registration indicate that our proposed method can produce accurate and optimized parameters of tensor registration with fastest speed relative to Genetic Algorithm and Particle Swarm Optimization.

Diffusion Tensor Tractography Reveals Abnormal Topological Organization in Structural Cortical Networks in Alzheimer's Disease

Recent research on Alzheimer's disease (AD) has shown that the decline of cognitive and memory functions is accompanied by a disrupted neuronal connectivity characterized by white matter (WM) degeneration. However, changes in the topological organization of WM structural network in AD remain largely unknown. Here, we used diffusion tensor image tractography to construct the human brain WM networks of 25 AD patients and 30 age- and sex-matched healthy controls, followed by a graph theoretical analysis. We found that both AD patients and controls had a small-world topology in WM network, suggesting an optimal balance between structurally segregated and integrative organization. More important, the AD patients exhibited increased shortest path length and decreased global efficiency in WM network compared with controls, implying abnormal topological organization. Furthermore, we showed that the WM network contained highly connected hub regions that were predominately located in the precuneus, cingulate cortex, and dorsolateral prefrontal cortex, which was consistent with the previous diffusion-MRI studies. Specifically, AD patients were found to have reduced nodal efficiency predominantly located in the frontal regions. Finally, we showed that the alterations of various network properties were significantly correlated with the behavior performances. Together, the present study demonstrated for the first time that the Alzheimer's brain was associated with disrupted topological organization in the large-scale WM structural networks, thus providing the structural evidence for abnormalities of systematic integrity in this disease. This work could also have implications for understanding how the abnormalities of structural connectivity in AD underlie behavioral deficits in the patients.

Improving contrast to noise ratio of resonance frequency contrast images (phase images) using balanced steady-state free precession

Recent MRI studies have exploited subtle magnetic susceptibility differences between brain tissues to improve anatomical contrast and resolution. These susceptibility differences lead to resonance frequency shifts which can be visualized by reconstructing the signal phase in conventional gradient echo (GRE) acquisition techniques. In this work, a method is proposed to improve the contrast to noise ratio per unit time (CNR efficiency) of anatomical MRI based on resonance frequency contrast. The method, based on the balanced steady-state free precession (bSSFP) MRI acquisition technique, was evaluated in its ability to generate contrast between gray and white matter in human brain at 3T and 7T. The results show substantially improved CNR efficiency of bSSFP phase images (2.85±0.21 times at 3T and 1.71±0.11 times at 7T) compared to the GRE data in a limited spatial area. This limited spatial coverage is attributed to the sensitivity of bSSFP to macroscopic B0 inhomogeneities. With this CNR improvement, high resolution bSSFP phase images (resolution=0.3×0.3×2mm3, acquisition time=10min) acquired at 3T had sufficient CNR to allow the visualization of cortical laminar structures in invivo human primary visual cortex. Practical application of the proposed method may require improvement of B0 homogeneity and stability by additional preparatory scans and/or compensation schemes such as respiration and drift compensation. Without these additions, the CNR benefits of the method may be limited to studies at low field or limited regions of interest.

Individual Differences in Subconscious Motor Control Predicted by GABA Concentration in SMA

Subliminal visual stimuli affect motor planning, but the size of such effects differs greatly between individuals. Here, we investigated whether such variation may be related to neurochemical differences between people. Cortical responsiveness is expected to be lower under the influence of more of the main inhibitory neurotransmitter, GABA. Thus, we hypothesized that, if an individual has more GABA in the supplementary motor area (SMA)--a region previously associated with automatic motor control--this would result in smaller subliminal effects. We measured the reversed masked prime--or negative compatibility--effect, and found that it correlated strongly with GABA concentration, measured with magnetic resonance spectroscopy. This occurred specifically in the SMA region, and not in other regions from which spectroscopy measurements were taken. We replicated these results in an independent cohort: more GABA in the SMA region is reliably associated with smaller effect size. These findings suggest that, across individuals, the responsiveness of subconscious motor mechanisms is related to GABA concentration in the SMA.

Experience-dependent plasticity of white-matter microstructure extends into old age

Experience-dependent alterations in the human brain's white-matter microstructure occur in early adulthood, but it is unknown whether such plasticity extends throughout life. We used cognitive training, diffusion-tensor imaging (DTI), and structural MRI to investigate plasticity of the white-matter tracts that connect the left and right hemisphere of the frontal lobes. Over a period of about 180 days, 20 younger adults and 12 older adults trained for a total of one hundred and one 1-h sessions on a set of three working memory, three episodic memory, and six perceptual speed tasks. Control groups were assessed at pre- and post-test. Training affected several DTI metrics and increased the area of the anterior part of the corpus callosum. These alterations were of similar magnitude in younger and older adults. The findings indicate that experience-dependent plasticity of white-matter microstructure extends into old age and that disruptions of structural interhemispheric connectivity in old age, which are pronounced in aging, are modifiable by experience and amenable to treatment.

Evaluation of fiber bundles across subjects through brain mapping and registration of diffusion tensor data

This paper presents a visualization and analysis framework for evaluating changes in structural organization of fiber bundles in human brain white matter. Statistical analysis of fiber bundle organization is conducted using an anisotropy measure, volume ratio (VR), which is ratio of anisotropic and isotropic components. Initially fiber bundles are tracked using a probabilistic algorithm starting from seed voxels. To ensure accurate selection of seed voxels and to prevent operator bias, a reference brain (MNI_152) is used when marking ROIs. Individual structural MRI brain scans are mapped to the reference using volumetric conformal parameterization. This mapping preserves topology and aligns features perfectly making it a robust and accurate registration technique. One-to-one mapping to the template allows ROI selection and subsequent transfer of ROI to structural MRI of subject. Affine registration coregisters structural MRI and DTI. Seed voxels are mapped to DTI using the resulting transformation parameters. To evaluate the proposed approach, MRI and DTI of 12 normal volunteers and 15 medial temporal lobe epilepsy patients are used. First, a statistical hypothesis testing is conducted to test for anisotropy changes in cingulum and fornix fiber bundles of epileptic patients. Experimental results reveal a 40% decrease in anisotropy levels of cingulum in patients compared to volunteers. They also show a 25% overall decrease in anisotropy of fornix. Secondly, shapes of the bundles are visualized in 3D illustrating that the bundles of epileptic patients are bumpy while those of normal volunteers are smooth.

Structural analysis of the complex between calmodulin and full-length myelin basic protein, an intrinsically disordered molecule

Myelin basic protein (MBP) is present between the cytoplasmic leaflets of the compact myelin membrane in both the peripheral and central nervous systems, and characterized to be intrinsically disordered in solution. One of the best-characterized protein ligands for MBP is calmodulin (CaM), a highly acidic calcium sensor. We pulled down MBP from human brain white matter as the major calcium-dependent CaM-binding protein. We then used full-length brain MBP, and a peptide from rodent MBP, to structurally characterize the MBP-CaM complex in solution by small-angle X-ray scattering, NMR spectroscopy, synchrotron radiation circular dichroism spectroscopy, and size exclusion chromatography. We determined 3D structures for the full-length protein-protein complex at different stoichiometries and detect ligand-induced folding of MBP. We also obtained thermodynamic data for the two CaM-binding sites of MBP, indicating that CaM does not collapse upon binding to MBP, and show that CaM and MBP colocalize in myelin sheaths. In addition, we analyzed the post-translational modifications of rat brain MBP, identifying a novel MBP modification, glucosylation. Our results provide a detailed picture of the MBP-CaM interaction, including a 3D model of the complex between full-length proteins.

Mapping the human brain white matter tracts relative to cortical and deep gray matter using diffusion tensor imaging at high spatial resolution

The mapping of the human brain white matter fiber networks relative to deep subcortical and cortical gray matter requires high spatial resolution which is challenged by the low signal-to-noise ratio. The purpose of this short report was to introduce a whole brain high spatial resolution diffusion tensor imaging (DTI) protocol that enabled for the first time the mapping of corticopontocerebellar, frontostriatal and thalamofrontal fiber pathways in addition to other limbic, commissural, association and projection white matter pathways relative to the segmented deep gray (e.g., caudate nuclei) and the cortical lobes. Our DTI acquisition protocol and analysis strategy provide important template for brain-behavior research and for teaching brain mapping and are clinically affordable for patient comfort.

Patterns of age-related water diffusion changes in human brain by concordance and discordance analysis.

In diffusion tensor imaging (DTI), interpreting changes in terms of fractional anisotropy (FA) and mean diffusivity or axial (D(||)) and radial (D(⊥)) diffusivity can be ambiguous. The main objective of this study was to gain insight into the heterogeneity of age-related diffusion changes in human brain white matter by analyzing relationships between the diffusion measures in terms of concordance and discordance instead of evaluating them separately, which is difficult to interpret. Fifty-one cognitively normal subjects (22-79 years old) were studied with DTI at 4 Tesla. Age was associated with widespread concordant changes of decreased FA and increased MD but in some regions significant FA reductions occurred discordant to MD changes. Prominent age-related FA reductions were primarily related to greater radial (D(⊥)) than axial (D(||)) diffusivity changes, potentially reflecting processes of demyelination. In conclusion, concordant/discordant changes of DTI indices provide additional characterization of white matter alterations that accompany normal aging.

Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter

Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.

Diffusion tensor quantification of the human midsagittal corpus callosum subdivisions across the lifespan

The midsagittal corpus callosum (CC) cross-sectional area subdivisions have been used as early and sensitive markers of human brain white matter connectivity, development, natural aging and disease. Despite the simplicity and conspicuity of the appearance of the CC on anatomical magnetic resonance imaging (MRI), the published quantitative MRI literature on its regional sex and age trajectories are contradictory. The availability of noninvasive quantitative methods to assess the CC regions across the human lifespan would help clarify its contribution to behavior and cognition. In this report, we extended the utility of a recently described semi-automated diffusion tensor imaging (DTI) tissue segmentation method to utilize the high orientation contrast of the CC on DTI. Using optimized DTI methods on a cohort of 121 right-handed children and adults aged 6–68 years, we examined the CC areas and corresponding DTI metrics of the different functionally specialized sectors of the CC. Both the area and fractional anisotropy metrics followed inverted U-shaped curves, while the mean and radial diffusivities followed U-curves reflecting white matter progressive and regressive myelination dynamics that continue into young adulthood.

Changes in white matter microstructure during adolescence

Postmortem histological studies have demonstrated that myelination in human brain white matter (WM) continues throughout adolescence and well into adulthood. We used in vivo diffusion-weighted magnetic resonance imaging to test for age-related WM changes in 42 adolescents and 20 young adults. Tract-Based Spatial Statistics (TBSS) analysis of the adolescent data identified widespread age-related increases in fractional anisotropy (FA) that were most significant in clusters including the body of the corpus callosum and right superior corona radiata. These changes were driven by changes in perpendicular, rather than parallel, diffusivity. These WM clusters were used as seeds for probabilistic tractography, allowing us to identify the regions as belonging to callosal, corticospinal, and prefrontal tracts. We also performed voxel-based morphometry-style analysis of conventional T1-weighted images to test for age-related changes in grey matter (GM). We identified a cluster including right middle frontal and precentral gyri that showed an age-related decrease in GM density through adolescence and connected with the tracts showing age-related WM FA increases. The GM density decrease was highly significantly correlated with the WM FA increase in the connected cluster. Age-related changes in FA were much less prominent in the young adult group, but we did find a significant age-related increase in FA in the right superior longitudinal fascicle, suggesting that structural development of this pathway continues into adulthood. Our results suggest that significant microstructural changes in WM continue throughout adolescence and are associated with corresponding age-related changes in cortical GM regions.

Measurement of GABA and contaminants in gray and white matter in human brain in vivo

A preliminary study of discrimination between GABA and macromolecules (MMs) in human brain by proton double quantum filtering (DQF) at 3.0 T in vivo is presented. GABA-tuned and MM-tuned DQ filters were designed with dual-band 180 degrees radiofrequency (RF) pulses that were tuned for selective refocusing of GABA (3.0 and 1.9 ppm) and putative MM resonances (3.0 and 1.7 ppm), respectively. GABA and putative MM signals were extracted from a combined analysis of the filtered mixture signals and the calculated editing yields. Unexpectedly, the GABA and putative MM signals exhibited a similar doublet linewidth at the optimized TE = 82 ms. Furthermore, substantial MM-tuned DQF signal remained at TE = 148 ms, indicating the presence of a component other than MM. With water segmentation data, the GABA-tuned and MM-tuned DQF measures from the medial prefrontal and left frontal lobes were combined to give the concentrations of GABA and the additional component as 1.1 +/- 0.1 and 0.8 +/- 0.1 mM (mean +/- SD, N=3) for gray matter (GM) and 0.4 +/- 0.1 and 0.7+/-0.1 mM (N=3) for white matter (WM), respectively.