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      Structural Brain Network Reorganization and Social Cognition Related to Adverse Perinatal Condition from Infancy to Early Adolescence

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          Abstract

          Adverse conditions during fetal life have been associated to both structural and functional changes in neurodevelopment from the neonatal period to adolescence. In this study, connectomics was used to assess the evolution of brain networks from infancy to early adolescence. Brain network reorganization over time in subjects who had suffered adverse perinatal conditions is characterized and related to neurodevelopment and cognition. Three cohorts of prematurely born infants and children (between 28 and 35 weeks of gestational age), including individuals with a birth weight appropriated for gestational age and with intrauterine growth restriction (IUGR), were evaluated at 1, 6, and 10 years of age, respectively. A common developmental trajectory of brain networks was identified in both control and IUGR groups: network efficiencies of the fractional anisotropy (FA)-weighted and normalized connectomes increase with age, which can be related to maturation and myelination of fiber connections while the number of connections decreases, which can be associated to an axonal pruning process and reorganization. Comparing subjects with or without IUGR, a similar pattern of network differences between groups was observed in the three developmental stages, mainly characterized by IUGR group having reduced brain network efficiencies in binary and FA-weighted connectomes and increased efficiencies in the connectome normalized by its total connection strength (FA). Associations between brain networks and neurobehavioral impairments were also evaluated showing a relationship between different network metrics and specific social cognition-related scores, as well as a higher risk of inattention/hyperactivity and/or executive functional disorders in IUGR children.

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          Most cited references53

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          Infant Brain Atlases from Neonates to 1- and 2-Year-Olds

          Background Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/.
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            A critical evaluation of sonar "crown-rump length" measurements.

            In a study to evaluate the reproducibility and accuracy of the sonar technique of measurement of the in vivo fetal crown-rump length (Robinson, 1973), a series of in vivo and in vitro experiments was performed in which the random and systematic errors inherent in the technique were assessed. The potential sources of random error were those of operator judgement, movement of the fetus and mother, machine sensitivity settings and measurement from the photograph; while the sources of systematic error were those of oscilloscope scale factor, and velocity calibration inaccuracies, and the effect of beam width. The overall effect of the random errors, that is, the reproducibility of the technique, was assessed in an in vivo blind trial in which three independent measurements were made of the fetus. In a series of 30 experiments the average standard deviation of the three readings was found to be 1.2 mm. Evaluation of the systematic errors by in vivo experimentation, on the other hand, showed that the basic sonar measurements were in error by an overestimate of 1 mm for the beam width effect and 3.7 per cent for the scale factor and velocity calibration errors. A weighted non-linear regression analysis of 334 measurements was performed in order to obtain a "curve of best fit" for the period covering 6 to 14 weeks of menstrual age. The values obtained were corrected for the systematic errors and compared with widely quoted anatomical figures. In the second part of this investigation the original data was further analyzed to determine on a statistical basis the accuracy of the technique as a method of estimating maturity. It was shown that such an estimate could be made to within 4.7 days with a 95 per cent probability on the basic of a single measurement, and to within 2.7 days if three independent measurements were made.
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              Rich-club organization of the newborn human brain.

              Combining diffusion magnetic resonance imaging and network analysis in the adult human brain has identified a set of highly connected cortical hubs that form a "rich club"--a high-cost, high-capacity backbone thought to enable efficient network communication. Rich-club architecture appears to be a persistent feature of the mature mammalian brain, but it is not known when this structure emerges during human development. In this longitudinal study we chart the emergence of structural organization in mid to late gestation. We demonstrate that a rich club of interconnected cortical hubs is already present by 30 wk gestation. Subsequently, until the time of normal birth, the principal development is a proliferation of connections between core hubs and the rest of the brain. We also consider the impact of environmental factors on early network development, and compare term-born neonates to preterm infants at term-equivalent age. Though rich-club organization remains intact following premature birth, we reveal significant disruptions in both in cortical-subcortical connectivity and short-distance corticocortical connections. Rich club organization is present well before the normal time of birth and may provide the fundamental structural architecture for the subsequent emergence of complex neurological functions. Premature exposure to the extrauterine environment is associated with altered network architecture and reduced network capacity, which may in part account for the high prevalence of cognitive problems in preterm infants.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                08 December 2016
                2016
                : 10
                : 560
                Affiliations
                [1] 1Fetal i+D, Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona Barcelona, Spain
                [2] 2Experimental 7T MRI Unit, Institut d'Investigacions Biomèdiques August Pi I Sunyer Barcelona, Spain
                [3] 3Signal Processing Laboratory 5, École Polytechnique Fédérale de Lausanne Lausanne, Switzerland
                [4] 4Division of Development and Growth. Department of Pediatrics, University Hospital of Geneva Geneva, Switzerland
                [5] 5Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London London, UK
                [6] 6Centre for Biomedical Research on Rare Diseases Barcelona, Spain
                [7] 7Department of Radiology, University Hospital Center and University of Lausanne Lausanne, Switzerland
                Author notes

                Edited by: John Vijay Sagar Kommu, National Institute of Mental Health and Neurosciences, India

                Reviewed by: Vivek Agarwal, King George's Medical University, India; Suhash Chakraborty, Hindustan Aeronautics Limited Hospital, India

                *Correspondence: Emma Muñoz-Moreno emunozm@ 123456clinic.ub.es

                This article was submitted to Child and Adolescent Psychiatry, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2016.00560
                5143343
                28008304
                ecae4880-76fb-4f92-a631-0c7638e92054
                Copyright © 2016 Muñoz-Moreno, Fischi-Gomez, Batalle, Borradori-Tolsa, Eixarch, Thiran, Gratacós and Hüppi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 May 2016
                : 21 November 2016
                Page count
                Figures: 4, Tables: 6, Equations: 0, References: 77, Pages: 15, Words: 11599
                Funding
                Funded by: Fondation Leenaards 10.13039/501100006387
                Award ID: 2667
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 10.13039/501100001711
                Award ID: 33CM30_140334
                Award ID: 32473B_135817
                Funded by: Instituto de Salud Carlos III 10.13039/501100004587
                Award ID: CD11/00048
                Award ID: PI13/01018
                Funded by: Cerebra 10.13039/501100002833
                Funded by: Centre d'Imagerie BioMédicale 10.13039/501100006391
                Funded by: École Polytechnique Fédérale de Lausanne 10.13039/501100001703
                Categories
                Neuroscience
                Original Research

                Neurosciences
                connectome,intrauterine growth retardation,birth weight,executive function,neurodevelopment,preterm infants

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