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      The relationship between biological and psychosocial risk factors and resting‐state functional connectivity in 2‐month‐old Bangladeshi infants: A feasibility and pilot study

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          Abstract

          Childhood poverty has been associated with structural and functional alterations in the developing brain. However, poverty does not alter brain development directly, but acts through associated biological or psychosocial risk factors (e.g. malnutrition, family conflict). Yet few studies have investigated risk factors in the context of infant neurodevelopment, and none have done so in low‐resource settings such as Bangladesh, where children are exposed to multiple, severe biological and psychosocial hazards. In this feasibility and pilot study, usable resting‐state fMRI data were acquired in infants from extremely poor ( n = 16) and (relatively) more affluent ( n = 16) families in Dhaka, Bangladesh. Whole‐brain intrinsic functional connectivity (iFC) was estimated using bilateral seeds in the amygdala, where iFC has shown susceptibility to early life stress, and in sensory areas, which have exhibited less susceptibility to early life hazards. Biological and psychosocial risk factors were examined for associations with iFC. Three resting‐state networks were identified in within‐group brain maps: medial temporal/striatal, visual, and auditory networks. Infants from extremely poor families compared with those from more affluent families exhibited greater (i.e. less negative) iFC in precuneus for amygdala seeds; however, no group differences in iFC were observed for sensory area seeds. Height‐for‐age, a proxy for malnutrition/infection, was not associated with amygdala/precuneus iFC, whereas prenatal family conflict was positively correlated. Findings suggest that it is feasible to conduct infant fMRI studies in low‐resource settings. Challenges and practical steps for successful implementations are discussed.

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          An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data.

          Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed. Copyright © 2012 Elsevier Inc. All rights reserved.
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            Poverty and common mental disorders in low and middle income countries: A systematic review.

            In spite of high levels of poverty in low and middle income countries (LMIC), and the high burden posed by common mental disorders (CMD), it is only in the last two decades that research has emerged that empirically addresses the relationship between poverty and CMD in these countries. We conducted a systematic review of the epidemiological literature in LMIC, with the aim of examining this relationship. Of 115 studies that were reviewed, most reported positive associations between a range of poverty indicators and CMD. In community-based studies, 73% and 79% of studies reported positive associations between a variety of poverty measures and CMD, 19% and 15% reported null associations and 8% and 6% reported negative associations, using bivariate and multivariate analyses respectively. However, closer examination of specific poverty dimensions revealed a complex picture, in which there was substantial variation between these dimensions. While variables such as education, food insecurity, housing, social class, socio-economic status and financial stress exhibit a relatively consistent and strong association with CMD, others such as income, employment and particularly consumption are more equivocal. There are several measurement and population factors that may explain variation in the strength of the relationship between poverty and CMD. By presenting a systematic review of the literature, this paper attempts to shift the debate from questions about whether poverty is associated with CMD in LMIC, to questions about which particular dimensions of poverty carry the strongest (or weakest) association. The relatively consistent association between CMD and a variety of poverty dimensions in LMIC serves to strengthen the case for the inclusion of mental health on the agenda of development agencies and in international targets such as the millenium development goals. Copyright 2010 Elsevier Ltd. All rights reserved.
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              A structural MRI study of human brain development from birth to 2 years.

              Brain development in the first 2 years after birth is extremely dynamic and likely plays an important role in neurodevelopmental disorders, including autism and schizophrenia. Knowledge regarding this period is currently quite limited. We studied structural brain development in healthy subjects from birth to 2. Ninety-eight children received structural MRI scans on a Siemens head-only 3T scanner with magnetization prepared rapid gradient echo T1-weighted, and turbo spin echo, dual-echo (proton density and T2 weighted) sequences: 84 children at 2-4 weeks, 35 at 1 year and 26 at 2 years of age. Tissue segmentation was accomplished using a novel automated approach. Lateral ventricle, caudate, and hippocampal volumes were also determined. Total brain volume increased 101% in the first year, with a 15% increase in the second. The majority of hemispheric growth was accounted for by gray matter, which increased 149% in the first year; hemispheric white matter volume increased by only 11%. Cerebellum volume increased 240% in the first year. Lateral ventricle volume increased 280% in the first year, with a small decrease in the second. The caudate increased 19% and the hippocampus 13% from age 1 to age 2. There was robust growth of the human brain in the first two years of life, driven mainly by gray matter growth. In contrast, white matter growth was much slower. Cerebellum volume also increased substantially in the first year of life. These results suggest the structural underpinnings of cognitive and motor development in early childhood, as well as the potential pathogenesis of neurodevelopmental disorders.

                Author and article information

                Contributors
                nadine.gaab@childrens.harvard.edu
                Journal
                Dev Sci
                Dev Sci
                10.1111/(ISSN)1467-7687
                DESC
                Developmental Science
                John Wiley and Sons Inc. (Hoboken )
                1363-755X
                1467-7687
                29 May 2019
                September 2019
                : 22
                : 5 , Global Child Development ( doiID: 10.1111/desc.v22.5 )
                : e12841
                Affiliations
                [ 1 ] Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine Boston Children’s Hospital Boston Massachusetts
                [ 2 ] Harvard Medical School Boston Massachusetts
                [ 3 ] College of Education and Human Sciences University of Nebraska‐Lincoln Lincoln Nebraska
                [ 4 ] Department of Neuroscience Brown University Providence Rhode Island
                [ 5 ] A.A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Boston Massachusetts
                [ 6 ] The International Centre for Diarrhoeal Disease Research Dhaka Bangladesh
                [ 7 ] National Institute of Neurosciences & Hospital Dhaka Bangladesh
                [ 8 ] Division of Infectious Diseases and International Health, Department of Medicine, School of Medicine University of Virginia Charlottesville Virginia
                [ 9 ] Harvard Graduate School of Education Cambridge Massachusetts
                Author notes
                [*] [* ] Correspondence

                Nadine Gaab, Department of Medicine/Division of Developmental Medicine, Boston Children’s Hospital, 1 Autumn Street (Office 643), Boston, MA 02115.

                Email: nadine.gaab@ 123456childrens.harvard.edu

                Article
                DESC12841
                10.1111/desc.12841
                6713583
                31016808
                6b3bc212-48a3-411e-89b5-95d127de6a7e
                © 2019 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 June 2018
                : 16 April 2019
                : 17 April 2019
                Page count
                Figures: 4, Tables: 3, Pages: 17, Words: 13912
                Funding
                Funded by: Bill and Melinda Gates Foundation
                Award ID: OPP1017093
                Award ID: OPP1111625
                Funded by: Henske Foundation
                Funded by: National Institute of Allergy and Infectious Diseases
                Award ID: AI043596-17
                Categories
                Special Issue Article
                Special Issue Articles
                Custom metadata
                2.0
                desc12841
                September 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.9 mode:remove_FC converted:01.10.2019

                Developmental biology
                Developmental biology

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