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      The Effects of Family Socioeconomic Status on Psychological and Neural Mechanisms as Well as Their Sex Differences

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          Abstract

          Family socioeconomic status (SES) is an important factor that affects an individual’s neural and cognitive development. The two novel aims of this study were to reveal (a) the effects of family SES on mean diffusivity (MD) using diffusion tensor imaging given the characteristic property of MD to reflect neural plasticity and development and (b) the sex differences in SES effects. In a study cohort of 1,216 normal young adults, we failed to find significant main effects of family SES on MD; however, previously observed main effects of family SES on regional gray matter volume and fractional anisotropy (FA) were partly replicated. We found a significant effect of the interaction between sex and family income on MD in the thalamus as well as significant effects of the interaction between sex and parents’ educational qualification (year’s of education) on MD and FA in the body of the corpus callosum as well as white matter areas between the anterior cingulate cortex and lateral prefrontal cortex. These results suggest the sex-specific associations of family SES with neural and/or cognitive mechanisms particularly in neural tissues in brain areas that play key roles in basic information processing and higher-order cognitive processes in a way females with greater family SES level show imaging outcome measures that have been associated with more neural tissues (such as greater FA and lower MD) and males showed opposite.

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          Most cited references54

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          Voxel-based morphometry--the methods.

          At its simplest, voxel-based morphometry (VBM) involves a voxel-wise comparison of the local concentration of gray matter between two groups of subjects. The procedure is relatively straightforward and involves spatially normalizing high-resolution images from all the subjects in the study into the same stereotactic space. This is followed by segmenting the gray matter from the spatially normalized images and smoothing the gray-matter segments. Voxel-wise parametric statistical tests which compare the smoothed gray-matter images from the two groups are performed. Corrections for multiple comparisons are made using the theory of Gaussian random fields. This paper describes the steps involved in VBM, with particular emphasis on segmenting gray matter from MR images with nonuniformity artifact. We provide evaluations of the assumptions that underpin the method, including the accuracy of the segmentation and the assumptions made about the statistical distribution of the data. Copyright 2000 Academic Press.
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            On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics

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              The subgenual anterior cingulate cortex in mood disorders.

              The anterior cingulate cortex (ACC) ventral to the genu of the corpus callosum has been implicated in the modulation of emotional behavior on the basis of neuroimaging studies in humans and lesion analyses in experimental animals. In a combined positron emission tomography/magnetic resonance imaging study of mood disorders, we demonstrated that the mean gray matter volume of this "subgenual" ACC (sgACC) cortex is abnormally reduced in subjects with major depressive disorder (MDD) and bipolar disorder, irrespective of mood state. Neuropathological assessments of sgACC tissue acquired postmortem from subjects with MDD or bipolar disorder confirmed the decrement in gray matter volume, and revealed that this abnormality was associated with a reduction in glia, with no equivalent loss of neurons. In positron emission tomography studies, the metabolic activity was elevated in this region in the depressed relative to the remitted phases of the same MDD subjects, and effective antidepressant treatment was associated with a reduction in sgACC activity. Other laboratories replicated and extended these findings, and the clinical importance of this treatment effect was underscored by a study showing that deep brain stimulation of the sgACC ameliorates depressive symptoms in treatment-resistant MDD. This article discusses the functional significance of these findings within the context of the preclinical literature that implicates the putative homologue of this region in the regulation of emotional behavior and stress response. In experimental animals, this region participates in an extended "visceromotor network" of structures that modulates autonomic/neuroendocrine responses and neurotransmitter transmission during the neural processing of reward, fear, and stress. These data thus hold important implications for the development of neural models of depression that can account for the abnormal motivational, neuroendocrine, autonomic, and emotional manifestations evident in human mood disorders.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                18 January 2019
                2018
                : 12
                : 543
                Affiliations
                [1] 1Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University , Sendai, Japan
                [2] 2Division of Medical Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University , Sendai, Japan
                [3] 3Department of Radiology and Nuclear Medicine, Institute of Development, Aging and Cancer, Tohoku University , Sendai, Japan
                [4] 4Creative Interdisciplinary Research Division, Frontier Research Institute for Interdisciplinary Sciences, Tohoku University , Sendai, Japan
                [5] 5Human and Social Response Research Division, International Research Institute of Disaster Science, Tohoku University , Sendai, Japan
                [6] 6Smart Ageing International Research Center, Institute of Development, Aging and Cancer, Tohoku University , Sendai, Japan
                [7] 7School of Medicine, Kobe University , Kobe, Japan
                [8] 8Division of Clinical Research, Medical-Industrial Translational Research Center, School of Medicine, Fukushima Medical University , Fukushima, Japan
                [9] 9Department of Functional Brain Science, Institute of Development, Aging and Cancer, Tohoku University , Sendai, Japan
                [10] 10Division of Psychiatry, Tohoku Medical and Pharmaceutical University , Sendai, Japan
                [11] 11Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry , Tokyo, Japan
                [12] 12Department of Psychiatry, Tohoku University School of Medicine , Sendai, Japan
                [13] 13Advantage Risk Management Co., Ltd. , Tokyo, Japan
                [14] 14Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo , Tokyo, Japan
                [15] 15Department of Ubiquitous Sensing, Institute of Development, Aging and Cancer, Tohoku University , Sendai, Japan
                [16] 16Department of Sport Science, School of Science and Technology, Nottingham Trent University , Nottingham, United Kingdom
                Author notes

                Edited by: Feng Kong, Shaanxi Normal University, China

                Reviewed by: Song Xue, Nanjing Normal University, China; Haijiang Li, Shanghai Normal University, China

                *Correspondence: Hikaru Takeuchi, takehi@ 123456idac.tohoku.ac.jp
                Article
                10.3389/fnhum.2018.00543
                6345688
                30713493
                db899ba9-38da-4886-860c-22516f582d0d
                Copyright © 2019 Takeuchi, Taki, Nouchi, Yokoyama, Kotozaki, Nakagawa, Sekiguchi, Iizuka, Yamamoto, Hanawa, Araki, Miyauchi, Sakaki, Nozawa, Ikeda, Yokota, Magistro, Sassa and Kawashima.

                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 July 2018
                : 31 December 2018
                Page count
                Figures: 6, Tables: 7, Equations: 0, References: 74, Pages: 18, Words: 0
                Funding
                Funded by: Ministry of Education, Culture, Sports, Science and Technology 10.13039/501100001700
                Award ID: KAKENHI 23700306
                Award ID: KAKENHI 25700012
                Categories
                Neuroscience
                Original Research

                Neurosciences
                family social economic status,voxel-based morphometry,diffusion tensor imaging,sex difference,family income,parents’ highest educational qualification

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