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      Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain

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          Abstract

          Background

          There has been a recent proliferation in neuroimaging research focusing on brain development in the prenatal, neonatal and very early childhood brain. Early brain injury and preterm birth are associated with increased risk of neurodevelopmental disorders, indicating the importance of this early period for later outcome.

          Scope and methodology

          Although using a wide range of different methodologies and investigating diverse samples, the common aim of many of these studies has been to both track normative development and investigate deviations in this development to predict behavioural, cognitive and neurological function in childhood. Here we review structural and functional neuroimaging studies investigating the developing brain. We focus on practical and technical complexities of studying this early age range and discuss how neuroimaging techniques have been successfully applied to investigate later neurodevelopmental outcome.

          Conclusions

          Neuroimaging markers of later outcome still have surprisingly low predictive power and their specificity to individual neurodevelopmental disorders is still under question. However, the field is still young, and substantial challenges to both acquiring and modeling neonatal data are being met.

          Abstract

          Read the Commentary on this article at doi: 10.1111/jcpp.12890

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          Most cited references148

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          Rich-club organization of the human connectome.

          The human brain is a complex network of interlinked regions. Recent studies have demonstrated the existence of a number of highly connected and highly central neocortical hub regions, regions that play a key role in global information integration between different parts of the network. The potential functional importance of these "brain hubs" is underscored by recent studies showing that disturbances of their structural and functional connectivity profile are linked to neuropathology. This study aims to map out both the subcortical and neocortical hubs of the brain and examine their mutual relationship, particularly their structural linkages. Here, we demonstrate that brain hubs form a so-called "rich club," characterized by a tendency for high-degree nodes to be more densely connected among themselves than nodes of a lower degree, providing important information on the higher-level topology of the brain network. Whole-brain structural networks of 21 subjects were reconstructed using diffusion tensor imaging data. Examining the connectivity profile of these networks revealed a group of 12 strongly interconnected bihemispheric hub regions, comprising the precuneus, superior frontal and superior parietal cortex, as well as the subcortical hippocampus, putamen, and thalamus. Importantly, these hub regions were found to be more densely interconnected than would be expected based solely on their degree, together forming a rich club. We discuss the potential functional implications of the rich-club organization of the human connectome, particularly in light of its role in information integration and in conferring robustness to its structural core.
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            Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution.

            Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.
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              Structural and functional brain networks: from connections to cognition.

              How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.
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                Author and article information

                Contributors
                ad.edwards@kcl.ac.uk
                Journal
                J Child Psychol Psychiatry
                J Child Psychol Psychiatry
                10.1111/(ISSN)1469-7610
                JCPP
                Journal of Child Psychology and Psychiatry, and Allied Disciplines
                John Wiley and Sons Inc. (Hoboken )
                0021-9630
                1469-7610
                03 November 2017
                April 2018
                : 59
                : 4 , Annual Research Review: Reimagining the environment in developmental psychopathology: from molecules to effective treatments ( doiID: 10.1111/jcpp.2018.59.issue-4 )
                : 350-371
                Affiliations
                [ 1 ] Centre for the Developing Brain School of Imaging Sciences & Biomedical Engineering King's College London London UK
                [ 2 ] Department of Neuroimaging Institute of Psychiatry, Psychology and Neuroscience King's College London London UK
                Author notes
                [*] [* ] Correspondence

                A. David Edwards, Centre for the Developing Brain, School of Imaging Sciences and Biomedical Engineering, St. Thomas’ Hospital, King's College London, London SE1 7EH, UK; Email: ad.edwards@ 123456kcl.ac.uk

                Author information
                http://orcid.org/0000-0003-2097-979X
                http://orcid.org/0000-0003-4801-7066
                http://orcid.org/0000-0002-8033-6959
                Article
                JCPP12838
                10.1111/jcpp.12838
                5900873
                29105061
                5df4ef38-5cef-4544-9ff3-26964df96860
                © 2017 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 October 2017
                Page count
                Figures: 3, Tables: 0, Pages: 22, Words: 18723
                Funding
                Funded by: Wellcome EPSRC Centre for Medical Engineering at King's College London
                Award ID: WT 203148/Z/16/Z
                Funded by: Medical Research Council
                Award ID: MR/K006355/1
                Award ID: MR/LO11530/1
                Funded by: Department of Health through an NIHR Comprehensive Biomedical Research Centre Award (to Guy's and St. Thomas’ National Health Service (NHS) Foundation Trust in partnership with King's College London and King's College Hospital NHS Foundation Trust
                Categories
                Annual Research Review
                Annual Research Reviews
                Custom metadata
                2.0
                jcpp12838
                April 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.3.4 mode:remove_FC converted:16.04.2018

                Clinical Psychology & Psychiatry
                prematurity,perinatal,neurodevelopmental disorders,neuroimaging,biomarkers

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