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      Dissecting the midlife crisis: disentangling social, personality and demographic determinants in social brain anatomy

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          Abstract

          In any stage of life, humans crave connection with other people. In midlife, transitions in social networks can relate to new leadership roles at work or becoming a caregiver for aging parents. Previous neuroimaging studies have pinpointed the medial prefrontal cortex (mPFC) to undergo structural remodelling during midlife. Social behavior, personality predisposition, and demographic profile all have intimate links to the mPFC according in largely disconnected literatures. Here, we explicitly estimated their unique associations with brain structure using a fully Bayesian framework. We weighed against each other a rich collection of 40 UK Biobank traits with their interindividual variation in social brain morphology in ~10,000 middle-aged participants. Household size and daily routines showed several of the largest effects in explaining variation in social brain regions. We also revealed male-biased effects in the dorsal mPFC and amygdala for job income, and a female-biased effect in the ventral mPFC for health satisfaction.

          Abstract

          Hannah Kiesow et al. combine 40 behavioral indicators and neuroimaging data from the UK Biobank to investigate how the transitions in midlife in the domains of social, personality, and demographic determinants impact brain anatomy. Through Bayesian analyses, the authors were able to disentangle which specific traits, relative to other considered candidate traits, contributed the most to explaining differences in social brain volume.

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          UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age

          Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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            Fast robust automated brain extraction.

            An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods. Copyright 2002 Wiley-Liss, Inc.
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              Loneliness and social isolation as risk factors for mortality: a meta-analytic review.

              Actual and perceived social isolation are both associated with increased risk for early mortality. In this meta-analytic review, our objective is to establish the overall and relative magnitude of social isolation and loneliness and to examine possible moderators. We conducted a literature search of studies (January 1980 to February 2014) using MEDLINE, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. The included studies provided quantitative data on mortality as affected by loneliness, social isolation, or living alone. Across studies in which several possible confounds were statistically controlled for, the weighted average effect sizes were as follows: social isolation odds ratio (OR) = 1.29, loneliness OR = 1.26, and living alone OR = 1.32, corresponding to an average of 29%, 26%, and 32% increased likelihood of mortality, respectively. We found no differences between measures of objective and subjective social isolation. Results remain consistent across gender, length of follow-up, and world region, but initial health status has an influence on the findings. Results also differ across participant age, with social deficits being more predictive of death in samples with an average age younger than 65 years. Overall, the influence of both objective and subjective social isolation on risk for mortality is comparable with well-established risk factors for mortality.
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                Author and article information

                Contributors
                danilo.bzdok@mcgill.ca
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                17 June 2021
                17 June 2021
                2021
                : 4
                : 728
                Affiliations
                [1 ]GRID grid.1957.a, ISNI 0000 0001 0728 696X, Department of Psychiatry, Psychotherapy, and Psychosomatics, , RWTH Aachen University, ; Aachen, Germany
                [2 ]GRID grid.26790.3a, ISNI 0000 0004 1936 8606, Department of Psychology, , University of Miami, ; Coral Gables, FL USA
                [3 ]GRID grid.14709.3b, ISNI 0000 0004 1936 8649, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, , McGill University, ; Montréal, QC Canada
                [4 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Psychology, , University of Pennsylvania, ; Philadelphia, PA USA
                [5 ]GRID grid.14709.3b, ISNI 0000 0004 1936 8649, Department of Biomedical Engineering, McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), Faculty of Medicine, , McGill University, ; Montréal, QC Canada
                [6 ]GRID grid.510486.e, Mila – Quebec Artificial Intelligence Institute, ; Montréal, QC Canada
                Author information
                http://orcid.org/0000-0001-9851-308X
                http://orcid.org/0000-0003-2278-8962
                http://orcid.org/0000-0001-9256-6041
                http://orcid.org/0000-0001-6495-9040
                http://orcid.org/0000-0003-3466-6620
                Article
                2206
                10.1038/s42003-021-02206-x
                8211729
                34140617
                80f34fad-b763-4324-822c-042a60572985
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 January 2021
                : 11 May 2021
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                © The Author(s) 2021

                computational biology and bioinformatics,neuroscience

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