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  • br Materials and methods br Results br Discussion

    2018-10-25


    Materials and methods
    Results
    Discussion The purpose of this study was to investigate neural mechanisms underlying deficits in visuospatial memory in young adults with a history of childhood poverty. While the relationship between childhood income and visuospatial memory performance mirrored previous reports (Evans and Schamberg, 2009; Herrmann and Guadagno, 1997) of adults with a history of childhood poverty performing more poorly on a visuospatial recognition task, this relationship did not reach significance in our sample. This is not entirely unexpected, as our study involving complex neuroimaging included less subjects than the studies that examined cognitive functions only. The interaction we observed between childhood income and hippocampal function on visuospatial memory performance reveals a novel and interesting link between hippocampal function in association with visuospatial memory performance and history of childhood poverty. We demonstrate here that toward higher levels of childhood income, there was an expected positive association between hippocampal activation and memory performance. Conversely, toward lower levels of childhood income, the association between memory performance and hippocampal activation was negative (i.e. more activation was associated with poorer memory performance). We did not detect an association between neural activation in the hippocampus during encoding and performance on the subsequent recognition task, across all the subjects, in selective androgen receptor modulators to a previous report of hippocampal engagement in both information encoding and recognition (Wong et al., 2013). These findings suggest a possible “disconnect” between hippocampal activation as observed on fMRI and performance on a visuospatial recognition task in adults with a history of poverty. One relatively straight forward explanation of our findings is that while increased activation in the higher childhood income participants reflects effective activation of hippocampus (i.e. stronger activation leads to better performance), activation in the lower childhood income participants reflects effort associated with difficulty that is not leading to improved performance. These results link previous findings, which separately documented associations between poverty and poorer memory performance (Farah et al., 2006; Noble et al., 2007), and poverty and hippocampal structure (Hanson et al., 2011). These findings are also consistent with data from the animal literature that rodents raised in conditions to model poverty had less capacity for plasticity in hippocampus, which was related to poorer performance on memory and learning tasks (Hackman et al., 2010). Exploratory analysis aimed to identify activation in other brain regions involved in encoding and recognition, associated with income or recognition accuracy. In our sample, multiple brain regions previously implicated in memory processes, like prefrontal cortex, inferior frontal gyrus, and visual cortex (Preston and Eichenbaum, 2013; Wong et al., 2013) were activated during encoding and recognition tasks, but none of these regions were associated with childhood income or recognition accuracy. There are important limitations of this study. Like the majority of studies examining early life risk factors, our study reveals links and associations, and should not be interpreted as evidence of causation. While the prospective and objective nature of the assessments confer confidence in our findings, they do not exclude the possibility of additional unaccounted factors contributing to the observed associations. Because poverty is a complex construct, encompassing multiple interacting variables like parental education, parenting style, school and home environment, nutrition, etc., it was not possible to isolate a single specific mechanism that influences brain function and cognitive performance. Mediation models may assist with this in the future, but our sample size provided limited power for this type of analysis. It is important to note here, that examining effects of isolated variables might not constitute the single best strategy either, since the interaction between multiple factors within the construct of childhood poverty might be the most salient contributing factor (Evans, 2003). In addition, we used a “convenience sample” from an existing longitudinal prospective cohort that had been followed up already for 15 years, and income was only measured at four year intervals beginning at age 9. Therefore, we chose the earliest possible data point available for this cohort. Although income in our sample and similar samples tends to remain stable over time (Evans and Schamberg, 2009), we are unable to provide direct evidence of early childhood poverty prior to age 9. We did not examine performance on other (non-visuospatial) memory tasks or other cognitive tasks, and do not know whether deficits in performance and/or the related differences in brain function would extend to other tasks. In addition, since subjects were tested only once as young adults, we were unable to investigate whether the reported deficits would persist into later adulthood.