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Experimental Aging Research
An International Journal Devoted to the Scientific Study of the Aging Process
Volume 46, 2020 - Issue 2
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Articles

Age-Related Changes in Verbal Working Memory Strategies

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Pages 93-127 | Received 31 May 2019, Accepted 29 Oct 2019, Published online: 23 Jan 2020
 

ABSTRACT

Background/Study context: Maintenance in verbal working memory is thought to rely on two main systems: a phonological and a semantic system. The three objectives of the present study were to clarify how these systems are organized and interact, to examine whether their involvement in maintenance changes with aging, and to identify which underlying mechanism accounts for both age-related changes in the available set of mechanisms and immediate recall.

Methods: To address these issues, we examined age-related changes in strategic aspects of maintenance of information in working memory. We collected trial-by-trial verbal reports of which strategy young and older adults used while accomplishing a verbal complex span task. In addition, individuals’ speed of articulation was collected.

Results: Results support the existence of separable systems (i.e., phonological and semantic systems) that participants combine to cope with increasing memory loads. We also found age-related differences (e.g., older individuals used more strategies than young individuals and used available strategies unequally often) and invariance (e.g., both age groups used strategies based on phonological and semantic processing) in strategic aspects of working memory maintenance. Importantly, articulation speed accounted for effects of both memory load and age on strategy distributions as well as for age-related differences in immediate recall.

Conclusion: Our findings suggest that young and older adults’ use of common and different sets of maintenance mechanisms stems for the constraints of the phonological loop in working memory, especially the speed of articulation, which slowed down with aging.

Acknowledgments

We thank Fleur Brun for her help in collecting, coding, and analyzing the data as well as Félicie Corminboeuf, Antoine Despond, and Mathilda Stritt for their help in data coding.

Additional information

Funding

This work was supported in part by the Centre National de la Recherche Scientifique (French National Science Foundation) and by a grant from the Agence Nationale de la Recherche [Grant # ANR-17-CE28-0003-01-01] to PL.

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