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      The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity

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          Abstract

          The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

          Abstract

          Stroke survivors require therapies that are tailored to their unique brain injury, but it is currently difficult to assess the degree to which damaged brain networks are engaged in mental activities. Lorenz et al. reveal how a novel brain-scanning tool can overcome this challenge in patients, paving the way to individualised therapy.

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          Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

          An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.
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            Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.

            Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. Copyright © 2011 Elsevier Inc. All rights reserved.
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              A default mode of brain function.

              A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
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                Author and article information

                Journal
                Brain
                Brain
                brainj
                Brain
                Oxford University Press
                0006-8950
                1460-2156
                July 2021
                18 March 2021
                18 March 2021
                : 144
                : 7
                : 2199-2213
                Affiliations
                [1 ]Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London , London SE1 7EH, UK
                [2 ]Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford , Oxford OX3 9DU, UK
                [3 ]Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London , London SE5 8AF, UK
                [4 ]Biomedical Image Analysis Group, Imperial College London , London SW7 2AZ, UK
                [5 ]Department of Paediatrics, University of Oxford , Oxford OX3 9DU, UK
                [6 ]Department of Bioengineering, Imperial College London , London SW7 2AZ, UK
                Author notes

                Dafnis Batalle and A David Edwards authors contributed equally to this work.

                Correspondence to: Dr Dafnis Batalle Department of Forensic and Neurodevelopmental Science Institute of Psychiatry, Psychology and Neuroscience King’s College London 16, De Crespigny Park, SE5 8AF, London, UK E-mail: dafnis.batalle@ 123456kcl.ac.uk Correspondence may also be addressed to: Professor David Edwards Centre for the Developing Brain School of Biomedical Engineering and Imaging Sciences King’s College London, London SE1 7EH, UK E-mail: ad.edwards@ 123456kcl.ac.uk
                Author information
                https://orcid.org/0000-0002-6704-5727
                https://orcid.org/0000-0001-7941-5230
                https://orcid.org/0000-0002-8214-116X
                https://orcid.org/0000-0002-3550-1644
                https://orcid.org/0000-0002-8033-6959
                https://orcid.org/0000-0003-2097-979X
                Article
                awab118
                10.1093/brain/awab118
                8370420
                33734321
                3b2fa842-94e7-4568-ba8f-db5776d83f55
                © The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 January 2020
                : 11 December 2020
                : 16 December 2020
                : 12 August 2021
                Page count
                Pages: 15
                Funding
                Funded by: European Research Council, DOI 10.13039/100010663;
                Funded by: European Union Seventh Framework Programme, DOI 10.13039/100011102;
                Award ID: FP/2007–2013
                Funded by: ERC, DOI 10.13039/100010663;
                Award ID: 319456
                Funded by: EPSRC, DOI 10.13039/501100000266;
                Award ID: WT 203148/Z/16/Z
                Funded by: Medical Research Council, DOI 10.13039/501100000265;
                Award ID: MR/K006355/1
                Award ID: MR/L011530/1
                Funded by: European Innovative Medicines Initiative Joint Undertaking;
                Award ID: 115300
                Award ID: 777394
                Funded by: European Union’s Seventh Framework Programme;
                Award ID: FP7/2007–2013
                Funded by: Medical Research Council, DOI 10.13039/501100000265;
                Funded by: Clinician Scientist Fellowship;
                Award ID: MR/P008712/1
                Funded by: Medical Research Council, DOI 10.13039/501100000265;
                Award ID: MR/N026063/1
                Funded by: Wellcome Trust, DOI 10.13039/100010269;
                Funded by: Royal Society, DOI 10.13039/501100000288;
                Award ID: 206675/Z/17/Z
                Funded by: Wellcome Trust Seed Award in Science;
                Award ID: 217316/Z/19/Z
                Funded by: NHS;
                Funded by: NIHR, DOI 10.13039/100006662;
                Categories
                Original Articles
                AcademicSubjects/MED00310
                AcademicSubjects/SCI01870

                Neurosciences
                neonatology,brain development,functional connectivity,resting-state connectivity,neuroanatomy

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