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      A latent measure explains substantial variance in white matter microstructure across the newborn human brain

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          Abstract

          A latent measure of white matter microstructure ( g WM) provides a neural basis for information processing speed and intelligence in adults, but the temporal emergence of g WM during human development is unknown. We provide evidence that substantial variance in white matter microstructure is shared across a range of major tracts in the newborn brain. Based on diffusion MRI scans from 145 neonates [gestational age (GA) at birth range 23 +2–41 +5 weeks], the microstructural properties of eight major white matter tracts were calculated using probabilistic neighborhood tractography. Principal component analyses (PCAs) were carried out on the correlations between the eight tracts, separately for four tract-averaged water diffusion parameters: fractional anisotropy, and mean, radial and axial diffusivities. For all four parameters, PCAs revealed a single latent variable that explained around half of the variance across all eight tracts, and all tracts showed positive loadings. We considered the impact of early environment on general microstructural properties, by comparing term-born infants with preterm infants at term equivalent age. We found significant associations between GA at birth and the latent measure for each water diffusion measure; this effect was most apparent in projection and commissural fibers. These data show that a latent measure of white matter microstructure is present in very early life, well before myelination is widespread. Early exposure to extra-uterine life is associated with altered general properties of white matter microstructure, which could explain the high prevalence of cognitive impairment experienced by children born preterm.

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          The online version of this article (doi:10.1007/s00429-017-1455-6) contains supplementary material, which is available to authorized users.

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          Most cited references63

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          cocor: A Comprehensive Solution for the Statistical Comparison of Correlations

          A valid comparison of the magnitude of two correlations requires researchers to directly contrast the correlations using an appropriate statistical test. In many popular statistics packages, however, tests for the significance of the difference between correlations are missing. To close this gap, we introduce cocor, a free software package for the R programming language. The cocor package covers a broad range of tests including the comparisons of independent and dependent correlations with either overlapping or nonoverlapping variables. The package also includes an implementation of Zou’s confidence interval for all of these comparisons. The platform independent cocor package enhances the R statistical computing environment and is available for scripting. Two different graphical user interfaces—a plugin for RKWard and a web interface—make cocor a convenient and user-friendly tool.
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            The processing-speed theory of adult age differences in cognition.

            A theory is proposed to account for some of the age-related differences reported in measures of Type A or fluid cognition. The central hypothesis in the theory is that increased age in adulthood is associated with a decrease in the speed with which many processing operations can be executed and that this reduction in speed leads to impairments in cognitive functioning because of what are termed the limited time mechanism and the simultaneity mechanism. That is, cognitive performance is degraded when processing is slow because relevant operations cannot be successfully executed (limited time) and because the products of early processing may no longer be available when later processing is complete (simultaneity). Several types of evidence, such as the discovery of considerable shared age-related variance across various measures of speed and large attenuation of the age-related influences on cognitive measures after statistical control of measures of speed, are consistent with this theory.
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              Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances.

              Brain injury in premature infants is of enormous public health importance because of the large number of such infants who survive with serious neurodevelopmental disability, including major cognitive deficits and motor disability. This type of brain injury is generally thought to consist primarily of periventricular leukomalacia (PVL), a distinctive form of cerebral white matter injury. Important new work shows that PVL is frequently accompanied by neuronal/axonal disease, affecting the cerebral white matter, thalamus, basal ganglia, cerebral cortex, brain stem, and cerebellum. This constellation of PVL and neuronal/axonal disease is sufficiently distinctive to be termed "encephalopathy of prematurity". The thesis of this Review is that the encephalopathy of prematurity is a complex amalgam of primary destructive disease and secondary maturational and trophic disturbances. This Review integrates the fascinating confluence of new insights into both brain injury and brain development during the human premature period.
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                Author and article information

                Contributors
                +44 (131) 242 2567 , james.boardman@ed.ac.uk
                Journal
                Brain Struct Funct
                Brain Struct Funct
                Brain Structure & Function
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1863-2653
                1863-2661
                6 June 2017
                6 June 2017
                2017
                : 222
                : 9
                : 4023-4033
                Affiliations
                [1 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, MRC Centre for Reproductive Health, , University of Edinburgh, ; 47 Little France Crescent, Edinburgh, EH16 4TJ UK
                [2 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, , University of Edinburgh, ; Edinburgh, EH8 9JZ UK
                [3 ]Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
                [4 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Centre for Clinical Brain Sciences, , University of Edinburgh, ; Chancellor’s Building, 49 Little France Crescent, Edinburgh, EH16 4SB UK
                [5 ]ISNI 0000 0004 4685 794X, GRID grid.415571.3, Department of Radiology, , Royal Hospital for Sick Children, ; 9 Sciennes Road, Edinburgh, EH9 1LF UK
                [6 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, University/BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, , University of Edinburgh, ; Edinburgh, EH16 4TJ UK
                [7 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Clinical Research Imaging Centre, Queen’s Medical Research Institute, , University of Edinburgh, ; Edinburgh, UK
                Author information
                http://orcid.org/0000-0003-3904-8960
                Article
                1455
                10.1007/s00429-017-1455-6
                5686254
                28589258
                f6a4233f-6ed6-440a-9505-dfe756ec6c20
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 12 October 2016
                : 24 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MRC G1002033
                Award ID: MR/M013111/1
                Award Recipient :
                Funded by: Theirworld
                Categories
                Original Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2017

                Neurology
                neonate,brain,magnetic resonance image,tractography,preterm
                Neurology
                neonate, brain, magnetic resonance image, tractography, preterm

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