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      Weak functional connectivity in the human fetal brain prior to preterm birth

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          Abstract

          It has been suggested that neurological problems more frequent in those born preterm are expressed prior to birth, but owing to technical limitations, this has been difficult to test in humans. We applied novel fetal resting-state functional MRI to measure brain function in 32 human fetuses in utero and found that systems-level neural functional connectivity was diminished in fetuses that would subsequently be born preterm. Neural connectivity was reduced in a left-hemisphere pre-language region, and the degree to which connectivity of this left language region extended to right-hemisphere homologs was positively associated with the time elapsed between fMRI assessment and delivery. These results provide the first evidence that altered functional connectivity in the preterm brain is identifiable before birth. They suggest that neurodevelopmental disorders associated with preterm birth may result from neurological insults that begin in utero.

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          Most cited references 93

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          A whole brain fMRI atlas generated via spatially constrained spectral clustering.

          Connectivity analyses and computational modeling of human brain function from fMRI data frequently require the specification of regions of interests (ROIs). Several analyses have relied on atlases derived from anatomical or cyto-architectonic boundaries to specify these ROIs, yet the suitability of atlases for resting state functional connectivity (FC) studies has yet to be established. This article introduces a data-driven method for generating an ROI atlas by parcellating whole brain resting-state fMRI data into spatially coherent regions of homogeneous FC. Several clustering statistics are used to compare methodological trade-offs as well as determine an adequate number of clusters. Additionally, we evaluate the suitability of the parcellation atlas against four ROI atlases (Talairach and Tournoux, Harvard-Oxford, Eickoff-Zilles, and Automatic Anatomical Labeling) and a random parcellation approach. The evaluated anatomical atlases exhibit poor ROI homogeneity and do not accurately reproduce FC patterns present at the voxel scale. In general, the proposed functional and random parcellations perform equivalently for most of the metrics evaluated. ROI size and hence the number of ROIs in a parcellation had the greatest impact on their suitability for FC analysis. With 200 or fewer ROIs, the resulting parcellations consist of ROIs with anatomic homology, and thus offer increased interpretability. Parcellation results containing higher numbers of ROIs (600 or 1,000) most accurately represent FC patterns present at the voxel scale and are preferable when interpretability can be sacrificed for accuracy. The resulting atlases and clustering software have been made publicly available at: http://www.nitrc.org/projects/cluster_roi/. Copyright © 2011 Wiley Periodicals, Inc.
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            Socioeconomic status and the developing brain.

            Childhood socioeconomic status (SES) is associated with cognitive achievement throughout life. How does SES relate to brain development, and what are the mechanisms by which SES might exert its influence? We review studies in which behavioral, electrophysiological and neuroimaging methods have been used to characterize SES disparities in neurocognitive function. These studies indicate that SES is an important predictor of neurocognitive performance, particularly of language and executive function, and that SES differences are found in neural processing even when performance levels are equal. Implications for basic cognitive neuroscience and for understanding and ameliorating the problems related to childhood poverty are discussed.
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              Cognitive and behavioral outcomes of school-aged children who were born preterm: a meta-analysis.

              The cognitive and behavioral outcomes of school-aged children who were born preterm have been reported extensively. Many of these studies have methodological flaws that preclude an accurate estimate of the long-term outcomes of prematurity. To estimate the effect of preterm birth on cognition and behavior in school-aged children. MEDLINE search (1980 to November 2001) for English-language articles, supplemented by a manual search of personal files maintained by 2 of the authors. We included case-control studies reporting cognitive and/or behavioral data of children who were born preterm and who were evaluated after their fifth birthday if the attrition rate was less than 30%. From the 227 reviewed studies, cognitive data from 15 studies and behavioral data from 16 studies were selected. Data on population demographics, study characteristics, and cognitive and behavioral outcomes were extracted from each study, entered in a customized database, and reviewed twice to minimize error. Differences between the mean cognitive scores of cases and controls were pooled. Homogeneity across studies was formally tested using a general variance-based method and graphically using Galbraith plots. Linear meta-analysis regression models were fitted to explore the impact of birth weight and gestational age on cognitive outcomes. Study-specific relative risks (RRs) were calculated for the incidence of attention-deficit/hyperactivity disorder (ADHD) and pooled. Quality assessment of the studies was performed based on a 10-point scale. Publication bias was examined using Begg modified funnel plots and formally tested using the Egger weighted-linear regression method. Among 1556 cases and 1720 controls, controls had significantly higher cognitive scores compared with children who were born preterm (weighted mean difference, 10.9; 95% confidence interval [CI], 9.2-12.5). The mean cognitive scores of preterm-born cases and term-born controls were directly proportional to their birth weight (R(2) = 0.51; P<.001) and gestational age (R(2) = 0.49; P<.001). Age at evaluation had no significant correlation with mean difference in cognitive scores (R(2) = 0.12; P =.20). Preterm-born children showed increases in externalizing and internalizing behaviors in 81% of studies and had more than twice the RR for developing ADHD (pooled RR, 2.64; 95% CI, 1.85-3.78). No differences were noted in cognition and behaviors based on the quality of the study. Children who were born preterm are at risk for reduced cognitive test scores and their immaturity at birth is directly proportional to the mean cognitive scores at school age. Preterm-born children also show an increased incidence of ADHD and other behaviors.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                09 January 2017
                2017
                : 7
                Affiliations
                [1 ]Merrill Palmer Skillman Institute for Child and Family Development, Wayne State University , Detroit, MI 48202, USA
                [2 ]Department of Pediatrics, Wayne State University School of Medicine , Detroit, MI 48202, USA
                [3 ]Perinatology Research Branch, NICHD/NIH/DHHS , Detroit, Michigan, and Bethesda, Maryland, USA
                [4 ]Institute for Social Research, Survey Research Center, University of Michigan , Ann Arbor, MI, 48104, USA
                [5 ]Department of Radiology & Biomedical Imaging, Yale School of Medicine , New Haven, CT 06520, USA
                [6 ]Department of Obstetrics and Gynecology, Wayne State University School of Medicine , Detroit, MI 48202, USA
                [7 ]Department of Neurosurgery, Yale School of Medicine , New Haven, CT 06520, USA
                [8 ]Department of Pediatrics, Yale School of Medicine , New Haven, CT 06520, USA
                [9 ]Department of Neurology, Yale School of Medicine , New Haven, CT 06520, USA
                [10 ]Center for Molecular Medicine, Wayne State University , Detroit, MI 48202, USA
                [11 ]Department of Obstetrics and Gynecology, University of Michigan School of Medicine , Ann Arbor, MI, 48104, USA
                [12 ]Department of Epidemiology, Michigan State University , East Lansing, MI 48825, USA.
                Author notes
                Article
                srep39286
                10.1038/srep39286
                5221666
                28067865
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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