65
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Development of the Cerebral Cortex across Adolescence: A Multisample Study of Inter-Related Longitudinal Changes in Cortical Volume, Surface Area, and Thickness

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Before we can assess and interpret how developmental changes in human brain structure relate to cognition, affect, and motivation, and how these processes are perturbed in clinical or at-risk populations, we must first precisely understand typical brain development and how changes in different structural components relate to each other. We conducted a multisample magnetic resonance imaging study to investigate the development of cortical volume, surface area, and thickness, as well as their inter-relationships, from late childhood to early adulthood (7–29 years) using four separate longitudinal samples including 388 participants and 854 total scans. These independent datasets were processed and quality-controlled using the same methods, but analyzed separately to study the replicability of the results across sample and image-acquisition characteristics. The results consistently showed widespread and regionally variable nonlinear decreases in cortical volume and thickness and comparably smaller steady decreases in surface area. Further, the dominant contributor to cortical volume reductions during adolescence was thinning. Finally, complex regional and topological patterns of associations between changes in surface area and thickness were observed. Positive relationships were seen in sulcal regions in prefrontal and temporal cortices, while negative relationships were seen mainly in gyral regions in more posterior cortices. Collectively, these results help resolve previous inconsistencies regarding the structural development of the cerebral cortex from childhood to adulthood, and provide novel insight into how changes in the different dimensions of the cortex in this period of life are inter-related.

          SIGNIFICANCE STATEMENT Different measures of brain anatomy develop differently across adolescence. Their precise trajectories and how they relate to each other throughout development are important to know if we are to fully understand both typical development and disorders involving aberrant brain development. However, our understanding of such trajectories and relationships is still incomplete. To provide accurate characterizations of how different measures of cortical structure develop, we performed an MRI investigation across four independent datasets. The most profound anatomical change in the cortex during adolescence was thinning, with the largest decreases observed in the parietal lobe. There were complex regional patterns of associations between changes in surface area and thickness, with positive relationships seen in sulcal regions in prefrontal and temporal cortices, and negative relationships seen mainly in gyral regions in more posterior cortices.

          Related collections

          Most cited references48

          • Record: found
          • Abstract: found
          • Article: not found

          A hybrid approach to the skull stripping problem in MRI.

          We present a novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models. Our method takes advantage of the robustness of the former as well as the surface information available to the latter. The algorithm first localizes a single white matter voxel in a T1-weighted MRI image, and uses it to create a global minimum in the white matter before applying a watershed algorithm with a preflooding height. The watershed algorithm builds an initial estimate of the brain volume based on the three-dimensional connectivity of the white matter. This first step is robust, and performs well in the presence of intensity nonuniformities and noise, but may erode parts of the cortex that abut bright nonbrain structures such as the eye sockets, or may remove parts of the cerebellum. To correct these inaccuracies, a surface deformation process fits a smooth surface to the masked volume, allowing the incorporation of geometric constraints into the skull-stripping procedure. A statistical atlas, generated from a set of accurately segmented brains, is used to validate and potentially correct the segmentation, and the MRI intensity values are locally re-estimated at the boundary of the brain. Finally, a high-resolution surface deformation is performed that accurately matches the outer boundary of the brain, resulting in a robust and automated procedure. Studies by our group and others outperform other publicly available skull-stripping tools. Copyright 2004 Elsevier Inc.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Specification of cerebral cortical areas.

            P Rakic (1988)
            How the immense population of neurons that constitute the human cerebral neocortex is generated from progenitors lining the cerebral ventricle and then distributed to appropriate layers of distinctive cytoarchitectonic areas can be explained by the radial unit hypothesis. According to this hypothesis, the ependymal layer of the embryonic cerebral ventricle consists of proliferative units that provide a proto-map of prospective cytoarchitectonic areas. The output of the proliferative units is translated via glial guides to the expanding cortex in the form of ontogenetic columns, whose final number for each area can be modified through interaction with afferent input. Data obtained through various advanced neurobiological techniques, including electron microscopy, immunocytochemistry, [3H]thymidine and receptor autoradiography, retrovirus gene transfer, neural transplants, and surgical or genetic manipulation of cortical development, furnish new details about the kinetics of cell proliferation, their lineage relationships, and phenotypic expression that favor this hypothesis. The radial unit model provides a framework for understanding cerebral evolution, epigenetic regulation of the parcellation of cytoarchitectonic areas, and insight into the pathogenesis of certain cortical disorders in humans.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex.

              Highly accurate surface models of the cerebral cortex are becoming increasingly important as tools in the investigation of the functional organization of the human brain. The construction of such models is difficult using current neuroimaging technology due to the high degree of cortical folding. Even single voxel misclassifications can result in erroneous connections being created between adjacent banks of a sulcus, resulting in a topologically inaccurate model. These topological defects cause the cortical model to no longer be homeomorphic to a sheet, preventing the accurate inflation, flattening, or spherical morphing of the reconstructed cortex. Surface deformation techniques can guarantee the topological correctness of a model, but are time-consuming and may result in geometrically inaccurate models. In order to address this need we have developed a technique for taking a model of the cortex, detecting and fixing the topological defects while leaving that majority of the model intact, resulting in a surface that is both geometrically accurate and topologically correct.
                Bookmark

                Author and article information

                Journal
                J Neurosci
                J. Neurosci
                jneuro
                jneurosci
                J. Neurosci
                The Journal of Neuroscience
                Society for Neuroscience
                0270-6474
                1529-2401
                22 March 2017
                22 March 2017
                : 37
                : 12
                : 3402-3412
                Affiliations
                [1] 1Department of Psychology, University of Oslo, 0317 Oslo, Norway,
                [2] 2Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90032,
                [3] 3Institute of Child Health and
                [4] 4Institute of Cognitive Neuroscience, University College London, London WC1N 1EH United Kingdom,
                [5] 5Brain and Development Research Center, Institute of Psychology, and
                [6] 6Leiden Institute for Brain and Cognition, Leiden University, 2300 RA Leiden, The Netherlands,
                [7] 7Institute of Human Development, University of California Berkeley, Berkeley, California 94720,
                [8] 8Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20814,
                [9] 9Children's Hospital of Los Angeles, Los Angeles, California 90027, and
                [10] 10Department of Psychology, University of Oregon, Eugene, Oregon 97403
                Author notes
                Correspondence should be addressed to Christian K. Tamnes, Department of Psychology, University of Oslo, P.O. Box 1094 Blindern, 0317 Oslo, Norway. c.k.tamnes@ 123456psykologi.uio.no

                Author contributions: C.K.T., S.-J.B., R.E.D., B.G., A.R., E.R.S., and E.A.C. designed research; C.K.T., M.M.H., A.-L.G., R.M., and K.L.M. performed research; C.K.T., M.M.H., A.-L.G., R.M., and K.L.M. analyzed data; C.K.T. wrote the paper.

                Author information
                http://orcid.org/0000-0002-1794-7132
                http://orcid.org/0000-0002-6463-186X
                Article
                3302-16
                10.1523/JNEUROSCI.3302-16.2017
                5373125
                28242797
                23ea0428-246e-44cb-be41-e724d2a9f879
                Copyright © 2017 Tamnes et al.

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

                History
                : 21 October 2016
                : 13 January 2017
                : 19 February 2017
                Categories
                Research Articles
                Development/Plasticity/Repair

                brain development,gray matter,morphometry,mri,replication
                brain development, gray matter, morphometry, mri, replication

                Comments

                Comment on this article