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      Cortical Thickness, Surface Area, and Gyrification Abnormalities in Children Exposed to Maltreatment: Neural Markers of Vulnerability?

      , , , , , ,
      Biological Psychiatry
      Elsevier BV

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          Abstract

          Childhood maltreatment has been shown to significantly elevate the risk of psychiatric disorder. Previous neuroimaging studies of children exposed to maltreatment have reported atypical neural structure in several regions, including the prefrontal cortex and temporal lobes. These studies have exclusively investigated volumetric differences rather than focusing on genetically and developmentally distinct indices of brain structure. Here we used surface-based methods to examine cortical thickness, surface area, and local gyrification in a community sample of children with documented experiences of abuse (n = 22) and a group of carefully matched nonmaltreated peers (n = 21). Reduced cortical thickness in the maltreated compared with the nonmaltreated group was observed in an extended cluster that incorporated the anterior cingulate, superior frontal gyrus, and orbitofrontal cortex. In addition, reduced cortical surface area was observed within the parcellated regions of the left middle temporal area and lingual gyrus. Local gyrification deficits within the maltreated group were located within two clusters, the lingual gyrus and the insula extending into pars opercularis. This is the first time structural abnormalities in the anterior cingulate and lingual gyrus have been detected in children exposed to maltreatment. Surface-based methods seem to capture subtle, previously undetected, morphological abnormalities associated with maltreatment. We suggest that these approaches detect developmental precursors of brain volume differences seen in adults with histories of abuse. Because the reported regions are implicated in several clinical disorders, they might constitute biological markers of vulnerability, linking exposure to early adversity and psychiatric risk. © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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          An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

          In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
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            Cortical surface-based analysis. I. Segmentation and surface reconstruction.

            Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.
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              The Strengths and Difficulties Questionnaire: A Research Note

                Author and article information

                Journal
                Biological Psychiatry
                Biological Psychiatry
                Elsevier BV
                00063223
                December 2013
                December 2013
                : 74
                : 11
                : 845-852
                Article
                10.1016/j.biopsych.2013.06.020
                23954109
                5a545332-34f0-4e4c-a43d-aabfa7cb5140
                © 2013

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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