The human brain undergoes dramatic structural change over the life span. In a large imaging cohort of 801 individuals aged 7–84 years, we applied quantitative relaxometry and diffusion microstructure imaging in combination with diffusion tractography to investigate tissue property dynamics across the human life span. Significant nonlinear aging effects were consistently observed across tracts and tissue measures. The age at which white matter (WM) fascicles attain peak maturation varies substantially across tissue measurements and tracts. These observations of heterochronicity and spatial heterogeneity of tract maturation highlight the importance of using multiple tissue measurements to investigate each region of the WM. Our data further provide additional quantitative evidence in support of the last‐in‐first‐out retrogenesis hypothesis of aging, demonstrating a strong correlational relationship between peak maturational timing and the extent of quadratic measurement differences across the life span for the most myelin sensitive measures. These findings present an important baseline from which to assess divergence from normative aging trends in developmental and degenerative disorders, and to further investigate the mechanisms connecting WM microstructure to cognition.

Abstract-The spectral radiance measured by an airborne imaging spectrometer for a material on the Earth's surface depends strongly on the illumination incident of the material and the atmospheric conditions. This dependence has limited the success of material-identification algorithms that rely on hyperspectral image data without associated ground-truth information. In this paper, we use a comprehensive physical model to show that the set of observed 0.4-2.5 m spectral-radiance vectors for a material lies in a low-dimensional subspace of the hyperspectral-measurement space. The physical model captures the dependence of the reflected sunlight, reflected skylight, and path-radiance terms on the scene geometry and on the distribution of atmospheric gases and aerosols over a wide range of conditions. Using the subspace model, we develop a local maximum-likelihood algorithm for automated material identification that is invariant to illumination, atmospheric conditions, and the scene geometry. The algorithm requires only the spectral reflectance of the target material as input. We show that the low dimensionality of material subspaces allows for the robust discrimination of a large number of materials over a wide range of conditions. We demonstrate the invariant algorithm for the automated identification of material samples in HYDICE imagery acquired under different illumination and atmospheric conditions.

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After 140 years from the discovery of Golgi’s black reaction, the study of connectivity of the cerebellum remains a fascinating yet challenging task. Current histological techniques provide powerful methods for unravelling local axonal architecture, but the relatively low volume of data that can be acquired in a reasonable amount of time limits their application to small samples. State-of-the-art in vivo magnetic resonance imaging (MRI) methods, such as diffusion tractography techniques, can reveal trajectories of the major white matter pathways, but their correspondence with underlying anatomy is yet to be established. Hence, a significant gap exists between these two approaches as neither of them can adequately describe the three-dimensional complexity of fibre architecture at the level of the mesoscale (from a few millimetres to micrometres). In this study, we report the application of MR diffusion histology and micro-tractography methods to reveal the combined cytoarchitectural organisation and connectivity of the human cerebellum at a resolution of 100-μm (2 nl/voxel volume). Results show that the diffusion characteristics for each layer of the cerebellar cortex correctly reflect the known cellular composition and its architectural pattern. Micro-tractography also reveals details of the axonal connectivity of individual cerebellar folia and the intra-cortical organisation of the different cerebellar layers. The direct correspondence between MR diffusion histology and micro-tractography with immunohistochemistry indicates that these approaches have the potential to complement traditional histology techniques by providing a non-destructive, quantitative and three-dimensional description of the microstructural organisation of the healthy and pathological tissue.

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Angle- and mass-resolved time-of-flight (TOF) measurements are used to probe the photodynamics and molecular orientation of C2H5Br on GaAs(110). Temperature-programmed desorption measurements indicate that this species is molecularly adsorbed with a binding energy of 0.43 eV. After photoinduced C−Br bond cleavage two channels for ethyl fragments ejected are observed in the TOF:  one resulting from direct ejection along the C−Br bond with a kinetic energy that varies from 0.6 to 1.1 eV, depending upon incident excitation wavelength, and the other, resulting from transient scattering from the surface potential energy well with a kinetic energy of 0.4 eV. Additionally, the kinetic energy of the directly ejected fragments varies with detection angle, a behavior consistent with a fragment−surface potential with normal energy scaling. The TOF measurements also indicate that, at coverages of <1 ML, the C2H5Br is oriented with the C−Br bond at an angle near 30° from the surface normal in the [01̄] direction. This result is in accord with earlier NEXAFS and TOF measurements and ab initio calculations of CH3Br on the same surface, which show that such a polar molecule is individually oriented by electrostatic interaction with the surface GaAs dipoles.

Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, 2013). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin‐Nets). The Myelin‐Nets were built from quantitative Magnetization Transfer data—an in‐vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin‐Nets. We therefore selected two age groups: Young‐Age (20–31 years old) and Old‐Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin‐Nets aging trajectory study. We found that the topological organization of the Myelin‐Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin‐Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging.