Childhood poverty is associated with altered hippocampal function and visuospatial memory in adulthood

Abstract

Childhood poverty is a risk factor for poorer cognitive performance during childhood and adulthood. While evidence linking childhood poverty and memory deficits in adulthood has been accumulating, underlying neural mechanisms are unknown. To investigate neurobiological links between childhood poverty and adult memory performance, we used functional magnetic resonance imaging (fMRI) during a visuospatial memory task in healthy young adults with varying income levels during childhood. Participants were assessed at age 9 and followed through young adulthood to assess income and related factors. During adulthood, participants completed a visuospatial memory task while undergoing MRI scanning. Patterns of neural activation, as well as memory recognition for items, were assessed to examine links between brain function and memory performance as it relates to childhood income. Our findings revealed associations between item recognition, childhood income level, and hippocampal activation. Specifically, the association between hippocampal activation and recognition accuracy varied as a function of childhood poverty, with positive associations at higher income levels, and negative associations at lower income levels. These prospective findings confirm previous retrospective results detailing deleterious effects of childhood poverty on adult memory performance. In addition, for the first time, we identify novel neurophysiological correlates of these deficits localized to hippocampus activation.

Time-varying effects of income on hippocampal volume trajectories in adolescent girls

“…In this context, we measured family income and parental education variables only in childhood, prior to the first scan; thus, we cannot say whether income and education levels were stable across the testing period, or whether they varied across adolescence. Even so, we note that other studies have similarly examined childhood SES and later neural development, and there is evidence that childhood SES has predictive power (e.g., Duval et al, 2017 ; Hair et al, 2015 ). While these factors limit our ability to generalize these findings to males and to more extreme ends of the wealth distribution, the restriction of our sample allowed us to avoid important confounds introduced by sex.…”

“…Thus, lower-SES children might exhibit hippocampal recovery over late adolescence and early adulthood. On the other hand, however, there is evidence that childhood poverty influences hippocampal function and associated memory-related functioning in adulthood ( Duval et al, 2017 ). While some longitudinal research has documented SES-related differences in trajectories of brain growth in infants ( Hanson et al, 2013 ), we know little about SES-related differences in hippocampal growth through adolescence.…”

Convergence of fMRI and ERP measures of emotional face processing in combat‐exposed U. S. military veterans

“…In line with prior work (e.g., Cuthbert et al, 2000;Foti et al, 2009;MacNamara, Foti, & Hajcak, 2009), the LPP was evident by 500 ms after stimulus onset at centropartial recording sites. 1 A 2-mm or higher cutoff for movement is widely used in the literature for task-based fMRI (e.g., Duval et al, 2017;Epstein et al, 2007;Gilat et al, 2017;Kim et al, 2013;MacNamara et al, 2015;Rabinak et al, 2014), especially with clinical samples, who may show more movement and are more difficult to recruit. Nonetheless, different types of data (e.g., resting state) may require more stringent parameters because, unlike task-based fMRI, motion artifacts are not suppressed by averaging (Caballero-Gaudes & Reynolds, 2017).…”

“… 1 A 2mm or higher cutoff for movement is widely used in the literature for task-based fMRI (e.g., Duval et al, 2017; Epstein et al, 2007; Gilat et al, 2017; Kim et al, 2013; MacNamara, Rabinak, et al, 2015; Rabinak et al, 2014), especially with clinical samples, who may show more movement and are more difficult to recruit. Nonetheless, different types of data (e.g., resting state) may require more stringent parameters, because unlike task-based fMRI, motion artifacts are not suppressed by averaging.…”

The Ethics of Medical Data Donation

“…As in the case of psychology and genomics, neuroscience research is largely based on data of individuals from WEIRD societies (Falk et al 2013), despite a plethora of studies showing that brain development is affected by socioeconomic status, early life stress, or cultural differences (Hackman et al 2010;Marshall et al 2018;Chan et al 2018;Duval et al 2017;Liddell and Jobson 2016). Indeed, within or across household socio-economic variables during childhood, such as family income, parental education (Ellwood-Lowe et al 2018;Weissman et al 2018) or neighbourhood poverty levels (Marshall et al 2018), can be traced on trajectories of brain development, and result in differences in brain structure (Ellwood-Lowe et al 2018) and cognitive functions (Hackman and Farah 2018), or gene expression (Parker et al 2017).…”