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. 2019 Mar;61(2):159-178.
doi: 10.1002/dev.21794. Epub 2018 Oct 30.

The relationship between cognitive enrichment and cognitive control: A systematic investigation of environmental influences on development through socioeconomic status

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The relationship between cognitive enrichment and cognitive control: A systematic investigation of environmental influences on development through socioeconomic status

Dima Amso et al. Dev Psychobiol. 2019 Mar.

Abstract

We measured the impact of socioeconomic status (SES) on cognitive processes. We examined cognitive control, specifically working memory (WM), in a sample of N = 141 7- to 17-year-olds using rule-guided behavior tasks. Our hypothesis is based on computational modeling data that suggest that the development of flexible cognitive control requires variable experiences in which to implement rule-guided action. We found that not all experiences that correlated with SES in our sample impacted task performance, and not all experiential variables that impacted performance were associated with SES. Of the experiential variables associated with task performance, only cognitive enrichment opportunities worked indirectly through SES to affect WM as tested with rule-guided behavior tasks. We discuss the data in the context of necessary precision in SES research.

Keywords: cognitive control; cognitive enrichment; socioeconomic status; working memory.

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Conflict of interest statement

CONFLIC T OF INTEREST

We have no conflicts to disclose.

Figures

FIGURE 1
FIGURE 1
Illustrates three tasks that parametrically manipulate working memory (WM) updating (through rule-order) and WM maintenance (through the number of alternatives maintained in WM for action). Across all tasks, performance costs on the 1 versus 2 blocks measure the cost of updating higher order rules into working memory for action as well as increasing WM maintenance, whereas performance on the 2 versus 4 blocks isolates the cost of WM maintenance. The Response task R1 block is a zero-order rule. A single response is correct for any stimulus. Correct response on R2 and R4 blocks requires updating of first-order rules into WM, where the color of the box indicates the correct response. The R4 block maintains the same first-order rule structure as R2, but adds additional alternatives for WM maintenance. The Feature and Dimension tasks follow the same logic. The Feature task F1 is a first-order rule block, while F2 and F4 are second-order blocks. Participants are instructed to determine whether the arrow is pointing in the right direction given the box color. Among the second-order F2 and F4 blocks, only the number of competing alternatives for WM maintenance (from 2 to 4) is increased. The Dimension Task D1 block is a second-order block, whereas D2 and D4 are third-order rule blocks. Participants are instructed to use the box color to then select a dimension (shape, orientation) to then match to an arrow direction. D2 and D4 are both third-order rule blocks, but D4 increases only the number of competing alternatives maintained in WM for action
FIGURE 2
FIGURE 2
Illustrates path model. We used separate models for each measure of socioeconomic status (household income, income-to-needs ratio, parents’ occupational level, and parents’ years of education) as well as for the outcomes of working memory (WM) tasks. Mediators and WM task data were selected based on hypothesized effects and significance in previous models
FIGURE 3
FIGURE 3
Response, Feature, and Dimension task performance for (a) RT (ms) and (b) accuracy (percent correct responses)
FIGURE 4
FIGURE 4
Simple correlations to illustrate the Feature task working memory (WM) updating performance for (a) accuracy and (b) reaction time costs (Block 2 − Block 1) as a function of Cognitive Enrichment subscale scores
FIGURE 5
FIGURE 5
Simple correlations to illustrate the Feature task accuracy for working memory (WM) maintenance (Block 4 − Block 2) as a function of Cognitive Enrichment subscale scores

References

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