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. 2017 Apr 28;5(2):17.
doi: 10.3390/jintelligence5020017.

Short-Term Storage and Executive Working Memory Processing Predict Fluid Intelligence in Primary School Children

Eva A Aeschlimann  1 , Annik E Voelke  2 , Claudia M Roebers  3
Affiliations

Short-Term Storage and Executive Working Memory Processing Predict Fluid Intelligence in Primary School Children

Eva A Aeschlimann et al. J Intell. .

Abstract

Working memory (WM) includes short-term storage and executive processing of information. WM has been suggested to be one of the key concepts to explain individual differences in fluid intelligence (Gf). However, only a few studies have investigated the association of the two different aspects of WM in relation to Gf. Furthermore, even fewer studies have included children. Therefore, we first investigated the inter-relations between the WM aspects (verbal and visual-spatial storage, verbal and visual-spatial executive processing). Second, we explored the relation between a general WM factor and Gf. Third, we analyzed the relations between the different WM aspects and Gf while we controlled for common variance among all WM tasks. Nine- to 11-year olds had to solve simple and complex span tasks. Correlations and structural equation modeling techniques were used to examine these relations. Most inter-relations among simple and complex spans were found to be substantial and positive. The general WM factor was related to Gf. Furthermore, after controlling for common variance among all WM tasks, individual differences in verbal storage, visual-spatial storage and verbal processing still uniquely related to Gf. Visual-spatial processing, however, was not related to Gf. Results are discussed in terms of underlying mechanisms.

Keywords: children; cognitive development; executive processing; fluid intelligence; intelligence; short-term storage; verbal and visual-spatial working memory.

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Conflict of interest statement

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Figures

Figure A1
Figure A1
Structural equation model (Model 1b) testing the relation between one working memory (WM) factor, age and fluid intelligence (Gf). Digit-FW = digit forward; Digit-BW = digit backward; Matrix-FW = matrix forward; Matrix-BW = matrix backward; CFT 1–4 = subtests of the CFT 20-R. All paths were significant (p < .05).
Figure A2
Figure A2
Structural equation model (Model 2b) testing the relations between working memory (WM) aspects, age and fluid intelligence (Gf). Digit-FW = digit forward; Digit-BW = digit backward; Matrix-FW = matrix forward; Matrix-BW = matrix backward; CFT 1–4 = subtests of the CFT 20-R. Solid lines represent significant paths (p < .05), dashed lines represent non-significant paths.
Figure 1
Figure 1
Correlations between age and the four WM aspects as well as partial correlations after controlling for age between the four WM aspects. Digit-FW = digit forward; Digit-BW = digit backward; Matrix-FW = matrix forward; and Matrix-BW = matrix backward. Solid lines represent significant correlations (p < .05), dashed lines represent non-significant correlations (p > .05).
Figure 2
Figure 2
Structural equation model (Model 1a) testing the relation between one working memory (WM) factor and fluid intelligence (Gf). Age (in months) was included as control variable. Digit-FW = digit forward; Digit-BW = digit backward; Matrix-FW = matrix forward; Matrix-BW = matrix backward; CFT 1–4 = subtests of the CFT 20-R. All paths were significant (p < .05).
Figure 3
Figure 3
Structural equation model (Model 2a) testing the relations between working memory (WM) aspects and fluid intelligence (Gf). Age (in months) was included as control variable. Digit-FW = digit forward; Digit-BW = digit backward; Matrix-FW = matrix forward; Matrix-BW = matrix backward; CFT 1–4 = subtests of the CFT 20-R. Solid lines represent significant paths (p < .05), dashed lines represent non-significant paths (p > .05).
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