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      Associations between Neighborhood SES and Functional Brain Network Development

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          Abstract

          Higher socioeconomic status (SES) in childhood is associated with stronger cognitive abilities, higher academic achievement, and lower incidence of mental illness later in development. While prior work has mapped the associations between neighborhood SES and brain structure, little is known about the relationship between SES and intrinsic neural dynamics. Here, we capitalize upon a large cross-sectional community-based sample (Philadelphia Neurodevelopmental Cohort, ages 8–22 years, n = 1012) to examine associations between age, SES, and functional brain network topology. We characterize this topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High-SES youth displayed stronger positive associations between age and clustering than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. The moderating effect of SES on positive associations between age and clustering was strongest for connections of intermediate length and was consistent with a stronger negative relationship between age and local connectivity in these regions in low-SES youth. Our findings suggest that, in late childhood and adolescence, neighborhood SES is associated with variation in the development of functional network structure in the human brain.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Rich-club organization of the human connectome.

            The human brain is a complex network of interlinked regions. Recent studies have demonstrated the existence of a number of highly connected and highly central neocortical hub regions, regions that play a key role in global information integration between different parts of the network. The potential functional importance of these "brain hubs" is underscored by recent studies showing that disturbances of their structural and functional connectivity profile are linked to neuropathology. This study aims to map out both the subcortical and neocortical hubs of the brain and examine their mutual relationship, particularly their structural linkages. Here, we demonstrate that brain hubs form a so-called "rich club," characterized by a tendency for high-degree nodes to be more densely connected among themselves than nodes of a lower degree, providing important information on the higher-level topology of the brain network. Whole-brain structural networks of 21 subjects were reconstructed using diffusion tensor imaging data. Examining the connectivity profile of these networks revealed a group of 12 strongly interconnected bihemispheric hub regions, comprising the precuneus, superior frontal and superior parietal cortex, as well as the subcortical hippocampus, putamen, and thalamus. Importantly, these hub regions were found to be more densely interconnected than would be expected based solely on their degree, together forming a rich club. We discuss the potential functional implications of the rich-club organization of the human connectome, particularly in light of its role in information integration and in conferring robustness to its structural core.
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              Situating the default-mode network along a principal gradient of macroscale cortical organization.

              Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.
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                Author and article information

                Journal
                Cereb Cortex
                Cereb. Cortex
                cercor
                Cerebral Cortex (New York, NY)
                Oxford University Press
                1047-3211
                1460-2199
                January 2020
                11 April 2019
                11 April 2019
                : 30
                : 1
                : 1-19
                Affiliations
                [1 ] Department of Neuroscience , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
                [2 ] Department of Psychology , College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
                [3 ] Department of Psychiatry , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
                [4 ] Department of Bioengineering , School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
                [5 ] Department of Neurology , Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
                [6 ] Department of Physics & Astronomy , College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
                [7 ] Department of Electrical & Systems Engineering , School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
                Author notes
                Address correspondence to Danielle S. Bassett, Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, 210 S. 33rd Street, 240 Skirkanich Hall, Philadelphia, PA 19104, USA. Email: dsb@ 123456seas.upenn.edu .
                Author information
                http://orcid.org/0000-0002-6183-4493
                Article
                bhz066
                10.1093/cercor/bhz066
                7029704
                31220218
                9d334af6-7bca-4282-b776-83cc088603d7
                © The Author(s) 2019. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 19
                Funding
                Funded by: Penn/CHOP Lifespan Brain Institute
                Funded by: National Science Foundation 10.13039/501100008982
                Award ID: BCS-1631550
                Award ID: NSF PHY-1554488
                Award ID: BCS-1430087
                Award ID: BCS-1441502
                Funded by: National Institute of Neurological Disorders and Stroke 10.13039/100000065
                Award ID: R01 NS099348
                Funded by: National Institute of Child Health and Human Development 10.13039/100000071
                Award ID: 1R01HD086888-01
                Funded by: National Institute of Mental Health 10.13039/100000025
                Award ID: R21-M MH-106799
                Award ID: R01-MH107235
                Award ID: R01-MH112847
                Award ID: 2-R01-DC-009209-11
                Funded by: Office of Naval Research 10.13039/100000006
                Funded by: Army Research Office 10.13039/100000183
                Award ID: DCIST-W911NF-17-2-0181
                Award ID: Grafton-W911NF-16-1-0474
                Award ID: Bassett-W911NF-14-1-0679
                Funded by: Army Research Laboratory 10.13039/100006754
                Award ID: W911NF-10-2-0022
                Funded by: Paul Allen Foundation
                Funded by: ISI Foundation
                Funded by: Alfred P. Sloan Foundation 10.13039/100000879
                Funded by: John D. and Catherine T. MacArthur Foundation 10.13039/100000870
                Categories
                Original Article

                Neurology
                development,fmri,graph theory,regional homogeneity,socioeconomic status
                Neurology
                development, fmri, graph theory, regional homogeneity, socioeconomic status

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