17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Sex differences in functional connectivity during fetal brain development

      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.

          Highlights

          • Limited research has assessed sex-related differences in fetal brain connectivity.

          • Functional connectivity (FC) data were collected from 118 human fetuses.

          • 16 distinct fetal FC networks were identified using a community detection algorithm.

          • Sex-related changes in fetal FC were examined using enrichment analysis.

          • We confirm for the first time that network FC differs with sex in utero.

          Abstract

          Sex-related differences in brain and behavior are apparent across the life course, but the exact set of processes that guide their emergence in utero remains a topic of vigorous scientific inquiry. Here, we evaluate sex and gestational age (GA)-related change in functional connectivity (FC) within and between brain wide networks. Using resting-state functional magnetic resonance imaging we examined FC in 118 human fetuses between 25.9 and 39.6 weeks GA (70 male; 48 female). Infomap was applied to the functional connectome to identify discrete prenatal brain networks in utero. A consensus procedure produced an optimal model comprised of 16 distinct fetal neural networks distributed throughout the cortex and subcortical regions. We used enrichment analysis to assess network-level clustering of strong FC-GA correlations separately in each sex group, and to identify network pairs exhibiting distinct patterns of GA-related change in FC between males and females. We discovered both within and between network FC-GA associations that varied with sex. Specifically, associations between GA and posterior cingulate-temporal pole and fronto-cerebellar FC were observed in females only, whereas the association between GA and increased intracerebellar FC was stronger in males. These observations confirm that sexual dimorphism in functional brain systems emerges during human gestation.

          Related collections

          Most cited references51

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

          Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant-level confound regression methods to limit its impact. However, many of the most commonly used techniques have not been systematically evaluated using a broad range of outcome measures. Here, we provide a systematic evaluation of 14 participant-level confound regression methods in 393 youths. Specifically, we compare methods according to four benchmarks, including the residual relationship between motion and connectivity, distance-dependent effects of motion on connectivity, network identifiability, and additional degrees of freedom lost in confound regression. Our results delineate two clear trade-offs among methods. First, methods that include global signal regression minimize the relationship between connectivity and motion, but result in distance-dependent artifact. In contrast, censoring methods mitigate both motion artifact and distance-dependence, but use additional degrees of freedom. Importantly, less effective de-noising methods are also unable to identify modular network structure in the connectome. Taken together, these results emphasize the heterogeneous efficacy of existing methods, and suggest that different confound regression strategies may be appropriate in the context of specific scientific goals.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Sexual dimorphism of brain developmental trajectories during childhood and adolescence.

            Human total brain size is consistently reported to be approximately 8-10% larger in males, although consensus on regionally specific differences is weak. Here, in the largest longitudinal pediatric neuroimaging study reported to date (829 scans from 387 subjects, ages 3 to 27 years), we demonstrate the importance of examining size-by-age trajectories of brain development rather than group averages across broad age ranges when assessing sexual dimorphism. Using magnetic resonance imaging (MRI) we found robust male/female differences in the shapes of trajectories with total cerebral volume peaking at age 10.5 in females and 14.5 in males. White matter increases throughout this 24-year period with males having a steeper rate of increase during adolescence. Both cortical and subcortical gray matter trajectories follow an inverted U shaped path with peak sizes 1 to 2 years earlier in females. These sexually dimorphic trajectories confirm the importance of longitudinal data in studies of brain development and underline the need to consider sex matching in studies of brain development.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              BrainSuite: an automated cortical surface identification tool.

              We describe a new magnetic resonance (MR) image analysis tool that produces cortical surface representations with spherical topology from MR images of the human brain. The tool provides a sequence of low-level operations in a single package that can produce accurate brain segmentations in clinical time. The tools include skull and scalp removal, image nonuniformity compensation, voxel-based tissue classification, topological correction, rendering, and editing functions. The collection of tools is designed to require minimal user interaction to produce cortical representations. In this paper we describe the theory of each stage of the cortical surface identification process. We then present classification validation results using real and phantom data. We also present a study of interoperator variability.
                Bookmark

                Author and article information

                Contributors
                Journal
                Dev Cogn Neurosci
                Dev Cogn Neurosci
                Developmental Cognitive Neuroscience
                Elsevier
                1878-9293
                1878-9307
                05 March 2019
                April 2019
                05 March 2019
                : 36
                : 100632
                Affiliations
                [a ]Department of Psychiatry, Washington University in St. Louis, St. Louis, United States
                [b ]Merrill Palmer Skillman Institute for Child and Family Development, Wayne State University, Detroit, United States
                [c ]Perinatology Research Branch, NICHD/NIH/DHHS, Bethesda, MD 20847, United States
                [d ]Perinatology Research Branch, NICHD/NIH/DHHS, Detroit, MI 48201, United States
                [e ]Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI 48202, United States
                [f ]Department of Physiology, Wayne State University School of Medicine, Detroit, MI 48202, United States
                [g ]Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, 48104, United States
                [h ]Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48825, United States
                [i ]Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI 48201, United States
                [j ]Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, United States
                [k ]Institute for Social Research, University of Michigan, Ann Arbor, MI 48109, United States
                Author notes
                [* ]Corresponding author at: Merrill Palmer Skillman Institute- Wayne State University, 71 E. Ferry Street, Detroit, MI 48009 United States. Moriah.Thomason@ 123456nyulangone.org
                [** ]Corresponding author at: Optical Radiology Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, C.B. 8225, 4515 McKinley Ave., St. Louis, MO, 63110, United States. aeggebre@ 123456wustl.edu
                Article
                S1878-9293(18)30124-5 100632
                10.1016/j.dcn.2019.100632
                6944279
                30901622
                84f957eb-6ec7-4edf-a232-d912d4f17f4f
                © 2019 Published by Elsevier Ltd.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 31 May 2018
                : 15 February 2019
                : 2 March 2019
                Categories
                Recent Advances in Developmental Cognitive Neuroscience – Special Issue from the Flux Congress 2016 & 2017

                Neurosciences
                connectivity,gestational age,mri,prenatal,resting-state,sex
                Neurosciences
                connectivity, gestational age, mri, prenatal, resting-state, sex

                Comments

                Comment on this article