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      Frontal pole–precuneus connectivity is associated with a discrepancy between self-rated and observer-rated depression severity in mood disorders: a resting-state functional magnetic resonance imaging study

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          Abstract

          Discrepancies in self-rated and observer-rated depression severity may underlie the basis for biological heterogeneity in depressive disorders and be an important predictor of outcomes and indicators to optimize intervention strategies. However, the neural mechanisms underlying this discrepancy have been understudied. This study aimed to examine the brain networks that represent the neural basis of the discrepancy between self-rated and observer-rated depression severity using resting-state functional MRI. To examine the discrepancy between self-rated and observer-rated depression severity, self- and observer-ratings discrepancy (SOD) was defined, and the higher and lower SOD groups were selected from depressed patients as participants showing extreme deviation. Resting-state functional MRI analysis was performed to examine regions with significant differences in functional connectivity in the two groups. The results showed that, in the higher SOD group compared to the lower SOD group, there was increased functional connectivity between the frontal pole and precuneus, both of which are subregions of the default mode network that have been reported to be associated with ruminative and self-referential thinking. These results provide insight into the association of brain circuitry with discrepancies between self- and observer-rated depression severity and may lead to more treatment-oriented diagnostic reclassification in the future.

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          The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

          L Radloff (1977)
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            A default mode of brain function.

            A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
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              Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

              Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method allows for interpretation of anticorrelations as there is no regression of the global signal. The toolbox implements fcMRI measures, such as estimation of seed-to-voxel and region of interest (ROI)-to-ROI functional correlations, as well as semipartial correlation and bivariate/multivariate regression analysis for multiple ROI sources, graph theoretical analysis, and novel voxel-to-voxel analysis of functional connectivity. We describe the methods implemented in the Conn toolbox for the analysis of fcMRI data, together with examples of use and interscan reliability estimates of all the implemented fcMRI measures. The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fcMRI measures.
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                Author and article information

                Contributors
                Journal
                Cereb Cortex
                Cereb Cortex
                cercor
                Cerebral Cortex (New York, NY)
                Oxford University Press
                1047-3211
                1460-2199
                July 2024
                25 July 2024
                25 July 2024
                : 34
                : 7
                : bhae284
                Affiliations
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS) , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Center for Diversity in Medical Education and Research (CDMER) , Graduate School of Medicine and Faculty of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS) , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
                University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM) , 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
                Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences , The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
                Department of Neuropsychiatry , Graduate School of Medicine, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
                The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS) , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
                Author notes
                Corresponding author: Naohiro Okada, International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, Japan. Email: nokada-tky@ 123456g.ecc.u-tokyo.ac.jp
                Author information
                https://orcid.org/0000-0002-8338-2758
                Article
                bhae284
                10.1093/cercor/bhae284
                11269430
                39049465
                bc27119e-d709-42ab-bc19-90f4ac2b6bbf
                © The Author(s) 2024. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://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
                : 08 February 2024
                : 10 June 2024
                : 03 July 2024
                Page count
                Pages: 10
                Funding
                Funded by: Moonshot R&D;
                Award ID: JPMJMS2021
                Funded by: AMED, DOI 10.13039/100009619;
                Award ID: JP23wm0625001
                Award ID: JP18dm0307004
                Award ID: JP18dm0307001
                Award ID: JP19dm0207069
                Funded by: JSPS KAKENHI;
                Award ID: JP22K18419
                Award ID: JP22H04926
                Award ID: JP21H05174
                Award ID: JP21H05171
                Award ID: JP20H03596
                Categories
                Original Article
                AcademicSubjects/MED00310
                AcademicSubjects/MED00385
                AcademicSubjects/SCI01870

                Neurology
                self-rated depression,observer-rated depression,discrepancy,frontal pole,precuneus
                Neurology
                self-rated depression, observer-rated depression, discrepancy, frontal pole, precuneus

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