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      Connectivity-Based Topographical Changes of the Corpus Callosum During Aging

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          Abstract

          Background: The corpus callosum (CC) is the most prominent white matter connection for interhemispheric information transfer. It is implicated in a variety of cognitive functions, which tend to decline with age. The region-specific projections of the fiber bundles with microstructural heterogeneity of the CC are associated with cognitive functions and diseases. However, how the CC is associated with the information transfer within functional networks and the connectivity changes during aging remain unclear. Studying the CC topography helps to understand the functional specialization and age-related changes of CC subregions.

          Methods: Diffusion tractography was used to subdivide the CC into seven subregions from 1,086 healthy volunteers within a wide age range (21–90 years), based on the connections to the cortical parcellations of the functional networks. Quantitative diffusion indices and connection probability were calculated to study the microstructure differences and age-related changes in the CC subregions.

          Results: According to the population-based probabilistic topography of the CC, part of the default mode network (DMN) and limbic network (LN) projected fibers through the genu and rostrum; the frontoparietal network (FPN), ventral attention network (VA) and somatomotor networks (SM) were interconnected by the CC body; callosal fibers arising from the part of the default mode network (DMN), dorsal attention network (DA) and visual network (VIS) passed through the splenium. Anterior CC subregions interconnecting DMN, LN, FPN, VA, and SM showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) than posterior CC subregions interconnecting DA and VIS. All the CC subregions showed slightly increasing FA and decreasing MD, RD, and axial diffusivity (AD) at younger ages and opposite trends at older ages. Besides, the anterior CC subregions exhibited larger microstructural and connectivity changes compared with the posterior CC subregions during aging.

          Conclusion: This study revealed the callosal subregions related to functional networks and uncovered an overall “anterior-to-posterior” region-specific changing trend during aging, which provides a baseline to identify the presence and timing of callosal connection states.

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          Most cited references70

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          "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician.

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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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              FreeSurfer.

              FreeSurfer is a suite of tools for the analysis of neuroimaging data that provides an array of algorithms to quantify the functional, connectional and structural properties of the human brain. It has evolved from a package primarily aimed at generating surface representations of the cerebral cortex into one that automatically creates models of most macroscopically visible structures in the human brain given any reasonable T1-weighted input image. It is freely available, runs on a wide variety of hardware and software platforms, and is open source. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                20 October 2021
                2021
                : 13
                : 753236
                Affiliations
                [1] 1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University , Shanghai, China
                [2] 2Institute of Neuroscience, National Yang Ming Chiao Tung University , Taipei, Taiwan
                [3] 3Center of Geriatrics and Gerontology, Taipei Veterans General Hospital , Taipei, Taiwan
                [4] 4Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University , Shanghai, China
                [5] 5Shanghai Changning Mental Health Center , Shanghai, China
                [6] 6Department of Psychiatry, Taipei Veterans General Hospital , Taipei, Taiwan
                [7] 7Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University , Taipei, Taiwan
                [8] 8Institute of Brain Science, National Yang Ming Chiao Tung University , Taipei, Taiwan
                [9] 9Aging and Health Research Center, National Yang Ming Chiao Tung University , Taipei, Taiwan
                [10] 10Taipei Municipal Gan-Dau Hospital , Taipei, Taiwan
                Author notes

                Edited by: Xiao-Xin Yan, Central South University, China

                Reviewed by: Leticia Rittner, State University of Campinas, Brazil; Mara Fabri, Marche Polytechnic University, Italy

                *Correspondence: Ching-Po Lin, cplin@ 123456ym.edu.tw
                Article
                10.3389/fnagi.2021.753236
                8565522
                34744693
                88dfb95b-a0d5-4680-8649-2694a42e47d3
                Copyright © 2021 Liu, Hsu, Huang, Zhang, Zhao, Tsai, Chen, Lin and Lo.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 August 2021
                : 28 September 2021
                Page count
                Figures: 4, Tables: 2, Equations: 5, References: 72, Pages: 13, Words: 10562
                Funding
                Funded by: Ministry of Science and Technology, Taiwan, doi 10.13039/501100004663;
                Award ID: MOST 110-2321-B-010-004
                Award ID: MOST 110-2321-B-010-007
                Award ID: MOST 110-2634-F-010-001
                Award ID: MOST 108-2321-B-010-010-MY2
                Funded by: National Key Research and Development Program of China, doi 10.13039/501100012166;
                Award ID: No. 2018YFC0910503
                Categories
                Neuroscience
                Original Research

                Neurosciences
                diffusion mri,tractography,functional networks,segmentation,atlas,aging trajectory
                Neurosciences
                diffusion mri, tractography, functional networks, segmentation, atlas, aging trajectory

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