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      Functional connectivity of the right inferior frontal gyrus and orbitofrontal cortex in depression

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          Abstract

          The orbitofrontal cortex extends into the laterally adjacent inferior frontal gyrus. We analyzed how voxel-level functional connectivity of the inferior frontal gyrus and orbitofrontal cortex is related to depression in 282 people with major depressive disorder (125 were unmedicated) and 254 controls, using FDR correction P < 0.05 for pairs of voxels. In the unmedicated group, higher functional connectivity was found of the right inferior frontal gyrus with voxels in the lateral and medial orbitofrontal cortex, cingulate cortex, temporal lobe, angular gyrus, precuneus, hippocampus and frontal gyri. In medicated patients, these functional connectivities were lower and toward those in controls. Functional connectivities between the lateral orbitofrontal cortex and the precuneus, posterior cingulate cortex, inferior frontal gyrus, ventromedial prefrontal cortex and the angular and middle frontal gyri were higher in unmedicated patients, and closer to controls in medicated patients. Medial orbitofrontal cortex voxels had lower functional connectivity with temporal cortex areas, the parahippocampal gyrus and fusiform gyrus, and medication did not result in these being closer to controls. These findings are consistent with the hypothesis that the orbitofrontal cortex is involved in depression, and can influence mood and behavior via the right inferior frontal gyrus, which projects to premotor cortical areas.

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          Most cited references34

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          Resting-state connectivity biomarkers define neurophysiological subtypes of depression

          Using functional MRI in a large multisite sample of more that 1,000 patients, four distinct neurophysiological biotypes of depression are defined. These biotypes are used to develop diagnostic classifiers that distinguish patients with depression from controls in separate multisite validation and replication cohorts, and can predict patient responsiveness to therapy.
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            Automated anatomical labelling atlas 3

            Following a first version AAL of the automated anatomical labeling atlas (Tzourio-Mazoyer et al., 2002), a second version (AAL2) (Rolls et al., 2015) was developed that provided an alternative parcellation of the orbitofrontal cortex following the description provided by Chiavaras, Petrides, and colleagues. We now provide a third version, AAL3, which adds a number of brain areas not previously defined, but of interest in many neuroimaging investigations. The 26 new areas in the third version are subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts; subdivision of the thalamus into 15 parts; the nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus, locus coeruleus, and raphe nuclei. The new atlas is available as a toolbox for SPM, and can be used with MRIcron.
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              A Brain-Wide Study of Age-Related Changes in Functional Connectivity.

              Aging affects functional connectivity between brain areas, however, a complete picture of how aging affects integration of information within and between functional networks is missing. We used complex network measures, derived from a brain-wide graph, to provide a comprehensive overview of age-related changes in functional connectivity. Functional connectivity in young and older participants was assessed during resting-state fMRI. The results show that aging has a large impact, not only on connectivity within functional networks but also on connectivity between the different functional networks in the brain. Brain networks in the elderly showed decreased modularity (less distinct functional networks) and decreased local efficiency. Connectivity decreased with age within networks supporting higher level cognitive functions, that is, within the default mode, cingulo-opercular and fronto-parietal control networks. Conversely, no changes in connectivity within the somatomotor and visual networks, networks implicated in primary information processing, were observed. Connectivity between these networks even increased with age. A brain-wide analysis approach of functional connectivity in the aging brain thus seems fundamental in understanding how age affects integration of information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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                Author and article information

                Journal
                Soc Cogn Affect Neurosci
                Soc Cogn Affect Neurosci
                scan
                Social Cognitive and Affective Neuroscience
                Oxford University Press
                1749-5016
                1749-5024
                January 2020
                28 January 2020
                28 January 2020
                : 15
                : 1
                : 75-86
                Affiliations
                [1 ] Institute of Science and Technology for Brain-inspired Intelligence , Fudan University, 200433, Shanghai, China
                [2 ] Department of Computer Science , University of Warwick, CV4 7AL, Coventry, UK
                [3 ] Oxford Centre for Computational Neuroscience , Oxford, UK
                [4 ] Department of Psychology , Southwest University, Chongqing, China
                [5 ] Key Laboratory of Cognition and Personality (SWU) , Ministry of Education, Chongqing, China
                [6 ] Institute of Neuroscience , Chongqing Medical University, Chongqing, China
                [7 ] Chongqing Key Laboratory of Neurobiology , Chongqing, China
                [8 ] Department of Neurology , Yongchuan Hospital of Chongqing Medical University, 402160, Chongqing, China
                [9 ] School of Mathematical Sciences , School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, 200433, Shanghai, China
                Author notes
                Correspondence should be addressed to: Wei Cheng. E-mail: wcheng@ 123456fudan.edu.cn

                Edmund T. Rolls, Wei Cheng, Jingnan Du, Dongtao Wei, Jiang Qiu, and Dan Dai contributed equally to this work.

                Author information
                http://orcid.org/0000-0003-3025-1292
                http://orcid.org/0000-0001-7591-5166
                Article
                nsaa014
                10.1093/scan/nsaa014
                7171374
                31993660
                3742e91d-b86d-4b98-821e-25c626fd9cf2
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 October 2019
                : 30 December 2019
                : 20 January 2020
                Page count
                Pages: 12
                Funding
                Funded by: 111 Project, DOI 10.13039/501100013314;
                Award ID: B18015
                Funded by: Shanghai Science & Technology;
                Award ID: 16JC1420402
                Funded by: National Key Research and Development Program of China, DOI 10.13039/501100012166;
                Award ID: 2018YFC1312900
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 91630314
                Funded by: Shanghai Municipal Science and Technology Major Project;
                Award ID: 2018SHZDZX01
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 81701773
                Award ID: 11771010
                Funded by: Shanghai Sailing Program;
                Award ID: 17YF1426200
                Funded by: Research Fund for the Doctoral Program of Higher Education of China, DOI 10.13039/501100013286;
                Award ID: 2017M610226
                Funded by: Natural Science Foundation of Shanghai, DOI 10.13039/100007219;
                Award ID: 18ZR1404400
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 31271087
                Award ID: 31470981
                Award ID: 31571137
                Award ID: 31500885
                Funded by: Program for the Top Young Talents;
                Funded by: Fundamental Research Funds for the Central Universities, DOI 10.13039/501100012226;
                Award ID: SWU1509383
                Funded by: Natural Science Foundation of Chongqing, DOI 10.13039/501100005230;
                Award ID: cstc2015jcyjA10106
                Funded by: China Postdoctoral Science Foundation, DOI 10.13039/501100002858;
                Award ID: 2015M572423
                Funded by: National Key Research and Development Program of China, DOI 10.13039/501100012166;
                Award ID: 2017YFA0505700
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 31300917
                Funded by: Chongqing Research Program of Basic Research and Frontier Technology, DOI 10.13039/501100013223;
                Award ID: cstc2016jcyjA0352
                Categories
                Original Manuscript

                Neurosciences
                depression,orbitofrontal cortex,inferior frontal gyrus,functional connectivity,inhibition,reward,non-reward,impulsivity

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