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      Neonatal White Matter Microstructure and Emotional Development during the Preschool Years in Children Who Were Born Very Preterm


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          Children born very preterm (<33 weeks of gestation) are at a higher risk of developing socio-emotional difficulties compared with those born at term. In this longitudinal study, we tested the hypothesis that diffusion characteristics of white matter (WM) tracts implicated in socio-emotional processing assessed in the neonatal period are associated with socio-emotional development in 151 very preterm children previously enrolled into the Evaluation of Preterm Imaging study (EudraCT 2009-011602-42). All children underwent diffusion tensor imaging at term-equivalent age and fractional anisotropy (FA) was quantified in the uncinate fasciculus (UF), inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus (SLF). Children’s socio-emotional development was evaluated at preschool age (median = 4.63 years). Exploratory factor analysis conducted on the outcome variables revealed a three-factor structure, with latent constructs summarized as: “emotion moderation,” “social function,” and “empathy.” Results of linear regression analyses, adjusting for full-scale IQ and clinical and socio-demographic variables, showed an association between lower FA in the right UF and higher “emotion moderation” scores (β = −0.280; p < 0.001), which was mainly driven by negative affectivity scores (β = −0.281; p = 0.001). Results further showed an association between higher full-scale IQ and better social functioning (β = −0.334, p < 0.001). Girls had higher empathy scores than boys (β = −0.341, p = 0.006). These findings suggest that early alterations of diffusion characteristics of the UF could represent a biological substrate underlying the link between very preterm birth and emotional dysregulation in childhood and beyond.

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          A new look at the statistical model identification

          IEEE Transactions on Automatic Control, 19(6), 716-723
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            FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford. For this NeuroImage special issue on "20 years of fMRI" we have been asked to write about the history, developments and current status of FSL. We also include some descriptions of parts of FSL that are not well covered in the existing literature. We hope that some of this content might be of interest to users of FSL, and also maybe to new research groups considering creating, releasing and supporting new software packages for brain image analysis. Copyright © 2011 Elsevier Inc. All rights reserved.
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              Fast robust automated brain extraction.

              An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods. Copyright 2002 Wiley-Liss, Inc.

                Author and article information

                Society for Neuroscience
                9 August 2021
                29 September 2021
                Sep-Oct 2021
                : 8
                : 5
                [1 ]Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London , London SE1 7EH, United Kingdom
                [2 ]Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London , London SE5 8AF, United Kingdom
                [3 ]MRC Centre for Neurodevelopmental Disorders , King’s College London, London SE1 1UL, United Kingdom
                Author notes

                The authors declare no competing financial interests.

                Author contributions: D.K., S.J.C., D.A.E., and C.N. designed research; D.K., L.D.V., D.P., L.H., S.F., and C.N. performed research; D.K., L.D.V., D.P., S.F., and C.N. analyzed data; D.K. and C.N. wrote the paper.

                This work was supported by Medical Research Council (United Kingdom) Grants MR/K006355/1, MR/L011530/1, and MR/S026460/1; the Wellcome/EPSRC Centre for Medical Engineering Grant WT 203148/Z/16/Z; the Biotechnology and Biological Sciences Research Council Grant BB/J014567/1; and the Action Medical Research and Dangoor Education Grant GN2606. This work uses data acquired during independent research funded by the National Institute for Health Research Programme Grants for Applied Research Programme (RP-PG-0707-10154).

                Correspondence should be addressed to Chiara Nosarti at chiara.nosarti@ 123456kcl.ac.uk .
                Copyright © 2021 Kanel et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                Page count
                Figures: 4, Tables: 5, Equations: 0, References: 92, Pages: 12, Words: 00
                Funded by: http://doi.org/10.13039/501100000265Medical Research Council (MRC)
                Award ID: MR/K006355/1
                Award ID: MR/L011530/1
                Award ID: MR/S026460/1
                Funded by: http://doi.org/10.13039/100010269Wellcome
                Award ID: WT 203148/Z/16/Z
                Funded by: http://doi.org/10.13039/501100000268Biotechnology and Biological Sciences Research Council (BBSRC)
                Award ID: BB/J014567/1
                Funded by: http://doi.org/10.13039/501100000317Action Medical Research (AMR)
                Award ID: GN2606
                Funded by: http://doi.org/10.13039/501100007602DH | NIHR | Programme Grants for Applied Research (NIHR Programme Grants for Applied Research)
                Award ID: RP-PG-0707-10154
                Research Article: New Research
                Cognition and Behavior
                Custom metadata
                September/October 2021

                diffusion mri,preterm children,socio-emotional development,tractography


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