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      Reorganization of brain structural networks in aging: A longitudinal study

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          Abstract

          Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age‐related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole‐brain or in specific networks, such as the resting‐state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub‐networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months ( SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age‐related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra‐hemispheric connections formed mainly by association fibers, while increases occur mostly in inter‐hemispheric connections and involve association, commissural, and projection fibers, supporting the last‐in‐first‐out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector‐hub inter‐modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.

          Abstract

          We followed a group of older adults longitudinally (mean interval time of 53 months) and characterized changes in white matter structural brain networks. We found decreases in intra‐hemispheric connections alongside with increases in inter‐hemispheric connections (a) and decrease in connector‐hub inter‐modular connectivity and increase of detected provincial hubs (b).

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          Most cited references138

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          Fast unfolding of communities in large networks

          Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008
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            Complex network measures of brain connectivity: uses and interpretations.

            Brain connectivity datasets comprise networks of brain regions connected by anatomical tracts or by functional associations. Complex network analysis-a new multidisciplinary approach to the study of complex systems-aims to characterize these brain networks with a small number of neurobiologically meaningful and easily computable measures. In this article, we discuss construction of brain networks from connectivity data and describe the most commonly used network measures of structural and functional connectivity. We describe measures that variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, characterize patterns of local anatomical circuitry, and test resilience of networks to insult. We discuss the issues surrounding comparison of structural and functional network connectivity, as well as comparison of networks across subjects. Finally, we describe a Matlab toolbox (http://www.brain-connectivity-toolbox.net) accompanying this article and containing a collection of complex network measures and large-scale neuroanatomical connectivity datasets. Copyright (c) 2009 Elsevier Inc. All rights reserved.
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              The organization of the human cerebral cortex estimated by intrinsic functional connectivity.

              Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
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                Author and article information

                Contributors
                njcsousa@med.uminho.pt
                Journal
                J Neurosci Res
                J Neurosci Res
                10.1002/(ISSN)1097-4547
                JNR
                Journal of Neuroscience Research
                John Wiley and Sons Inc. (Hoboken )
                0360-4012
                1097-4547
                02 February 2021
                May 2021
                : 99
                : 5 ( doiID: 10.1002/jnr.v99.5 )
                : 1354-1376
                Affiliations
                [ 1 ] Life and Health Sciences Research Institute (ICVS), School of Medicine University of Minho Braga Portugal
                [ 2 ] ICVS/3B’s, PT Government Associate Laboratory Braga/Guimarães Portugal
                [ 3 ] Clinical Academic Center – Braga Braga Portugal
                [ 4 ] Center for Music in the Brain (MIB) Aarhus University Aarhus Denmark
                [ 5 ] Department of Psychiatry University of Oxford Oxford UK
                Author notes
                [*] [* ] Correspondence

                Nuno Sousa, Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710‐057 Braga, Portugal.

                Email: njcsousa@ 123456med.uminho.pt

                Author information
                https://orcid.org/0000-0001-8489-5750
                Article
                JNR24795
                10.1002/jnr.24795
                8248023
                33527512
                a58b4fe0-2066-4cc5-b68d-c652be2568c7
                © 2021 The Authors. Journal of Neuroscience Research published by Wiley Periodicals LLC

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 November 2020
                : 31 December 2020
                Page count
                Figures: 9, Tables: 5, Pages: 23, Words: 17237
                Funding
                Funded by: Fundação para a Ciência e a Tecnologia , open-funder-registry 10.13039/501100001871;
                Funded by: European Regional Development Fund , open-funder-registry 10.13039/501100008530;
                Funded by: FP7 Health , open-funder-registry 10.13039/100011272;
                Funded by: Fundação Calouste Gulbenkian , open-funder-registry 10.13039/501100005635;
                Funded by: European Social Fund , open-funder-registry 10.13039/501100004895;
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                May 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:01.07.2021

                Neurosciences
                aging,cognitive performance,diffusion mri,network,white matter
                Neurosciences
                aging, cognitive performance, diffusion mri, network, white matter

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