Martha J. Farah’s research while affiliated with University of Pennsylvania and other places

Highly portable and accessible MRI technology will allow researchers to conduct field-based MRI research in community settings. Previous guidance for researchers working with fixed MRI does not address the novel ethical, legal, and societal issues (ELSI) of portable MRI (pMRI). Our interdisciplinary Working Group (WG) previously identified 15 core ELSI challenges associated with pMRI research and recommended solutions. In this article, we distill those detailed recommendations into a Portable MRI Research ELSI Checklist that offers practical operational guidance for researchers contemplating using this technology.

People of low socioeconomic status (SES) are often underrepresented in biomedical research. The importance of demographically diverse research samples is widely recognized, especially given socioeconomic disparities in health, but have been challenging to achieve. One barrier to research participation by low SES individuals is their distance from research centers and the difficulty of traveling. This article examines the promise of portable magnetic resonance imaging (pMRI) for enrolling participants of diverse SES in structural neuroimaging studies, and anticipates some of the challenges, practical and ethical, that may arise in the course of such research.

Researchers are rapidly developing and deploying highly portable MRI technology to conduct field-based research. The new technology will widen access to include new investigators in remote and unconventional settings and will facilitate greater inclusion of rural, economically disadvantaged, and historically underrepresented populations. To address the ethical, legal, and societal issues raised by highly accessible and portable MRI, an interdisciplinary Working Group (WG) engaged in a multi-year structured process of analysis and consensus building, informed by empirical research on the perspectives of experts and the general public. This article presents the WG’s consensus recommendations. These recommendations address technology quality control, design and oversight of research, including safety of research participants and others in the scanning environment, engagement of diverse participants, therapeutic misconception, use of artificial intelligence algorithms to acquire and analyze MRI data, data privacy and security, return of results and managing incidental findings, and research participant data access and control.

Why is lower socioeconomic status associated with higher rates of depression? And, is the surplus of depression at lower SES just more of the same type as depression found at higher levels, or is it distinctive? We addressed these questions by examining the relations among SES, amygdala volume, and symptoms of depression in healthy young adults. Amygdala volume, a risk factor for depression, does not synergize with SES in a diathesis-stress relation, nor does it mediate the relation of SES to depression. Rather, SES and amygdala volume are independent, additive risk factors. They are also associated with different depression symptoms and, whereas perceived stress fully mediates the relation of SES to depression, it has no relation to amygdala volume. These findings suggest heterogeneity of depression across the socioeconomic spectrum, with implications for treatment selection as well as for future genetic and brain studies.

Low socioeconomic status (SES) is associated with higher rates of emotional disorders in childhood and beyond. Here we assessed one possible contributor to this disparity, a cognitive bias in the interpretation of negative events, in a group of 341 9-year-olds (49% female, 94% White) ranging widely in SES. This cognitive bias, known as pessimism in the attributional style literature, is the tendency to interpret negative events as persistent (Stable) and pervasive (Global). It was found to be more common among lower SES children (effect sizes = 0.18–0.24 depending on SES measures: income to needs ratio, proportion of poverty from birth to age 9, and parental educational attainment). Moreover, persistent, pervasive adversity in children’s lives predicted this bias and mediated the SES—pessimism link. Pessimistic attributional style, in turn, was related to childhood emotional problems and mediated the relation between SES and these problems. Finally, evidence for serial mediation of the SES-mental health problems relationship was found via persistent, pervasive adversity and pessimism, respectively.

Growing up in poverty is associated with a heightened risk for mental and physical health problems across the life span, and there is a growing recognition of the role that social determinants of health play in driving these outcomes and inequities. How do the social conditions of poverty get under the skin to influence biology, and through what mechanisms do the stressors of poverty generate risk for a broad range of health problems? The growing field examining the neuroscience of socioeconomic status (SES) proposes that the brain is an entry point or pathway through which poverty and adversity become embedded in biology to generate these disparities. To date, however, the majority of research on the neuroscience of SES has focused on cognitive or executive control processes. However, the relationship between SES and brain systems involved in affective or emotional processes may be especially important for understanding social determinants of health. Accordingly, this Special Focus on The Affective Neuroscience of Poverty invited contributions from authors examining the relationship between SES and brain systems involved in generating and regulating emotions. In this editorial introduction, we (a) provide an overview of the neuroscience of SES; (b) introduce each of the articles in this Special Focus; and (c) discuss the scientific, treatment, and policy implications of studying the affective neuroscience of poverty.

Here, we test three often proposed hypotheses about socioeconomic status (SES), affect, and the brain, for which evidence is mixed or lacking. The first hypothesis, that negative affect is more common at lower levels of SES, has ample evidence from studies of psychiatric symptoms but is tested for the first time here across multiple measures of negative emotions in healthy young adults. The second hypothesis is actually a set of hypotheses, that SES is associated with three structural and functional properties of the amygdala. Third, and most important for the affective neuroscience of SES, is the hypothesis that SES differences in the amygdala are responsible for the affective differences. Despite the intuitive appeal of this hypothesis, it has rarely been tested and has never been confirmed. Here, we review the literature for evidence on each of these hypotheses and find in a number of cases that the evidence is weak or nonexistant. We then subject each hypothesis to a new empirical test with a large sample of healthy young adults. We confirm that negative affect is more common at lower levels of SES and we find a positive relation between SES and amygdala volume. However, evidence is weak on the relation of SES to functional properties of amygdala. Finally, the tendency toward negative affect in lower SES individuals cannot be accounted for by the structural or functional characteristics of the amygdala measured here.

Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (n ≈ 10,000 UK Biobank participants). Individuals with higher SES, compared to those with lower SES, showed a pattern of increased region volumes in the left brain and decreased region volumes in the right brain. The analogous lateralization pattern emerged for the fiber structure of anatomical white matter tracts. Our multimodal findings suggest hemispheric asymmetry as an SES-related brain signature, which was consistent across six different indicators of SES: degree, education, income, job, neighborhood, and vehicle count. Hence, hemispheric specialization may have evolved in human primates in a way that reveals crucial links to socioeconomic status.

Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (n ≈ 10,000 UK Biobank participants). Individuals with higher SES, compared to those with lower SES, showed a pattern of increased region volumes in the left brain and decreased region volumes in the right brain. The analogous lateralization pattern emerged for the fiber structure of anatomical white matter tracts. Our multimodal findings suggest hemispheric asymmetry as an SES-related brain signature, which was consistent across six different indicators of SES: degree, education, income, job, neighborhood, and vehicle count. Hence, hemispheric specialization may have evolved in human primates in a way that reveals crucial links to socioeconomic status.

Socioeconomic status (SES) correlates with brain structure, a relation of interest given the long-observed relations of SES to cognitive abilities and health. Yet, major questions remain open, in particular, the pattern of causality that underlies this relation. In an unprecedently large study, here, we assess genetic and environmental contributions to SES differences in neuroanatomy. We first establish robust SES-gray matter relations across a number of brain regions, cortical and subcortical. These regional correlates are parsed into predominantly genetic factors and those potentially due to the environment. We show that genetic effects are stronger in some areas (prefrontal cortex, insula) than others. In areas showing less genetic effect (cerebellum, lateral temporal), environmental factors are likely to be influential. Our results imply a complex interplay of genetic and environmental factors that influence the SES-brain relation and may eventually provide insights relevant to policy.