Freeing Capacity in Working Memory (WM) through the Use of Long-Term Memory (LTM) Representations

Saved in:
Bibliographic Details
Title: Freeing Capacity in Working Memory (WM) through the Use of Long-Term Memory (LTM) Representations
Language: English
Authors: Bartsch, Lea M. (ORCID 0000-0001-7640-9193), Shepherdson, Peter
Source: Journal of Experimental Psychology: Learning, Memory, and Cognition. Apr 2022 48(4):465-482.
Availability: American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org
Peer Reviewed: Y
Page Count: 18
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Descriptors: Short Term Memory, Task Analysis, Recall (Psychology), German, Native Language, Vocabulary, Foreign Countries, Associative Learning, Cognitive Ability, Bayesian Statistics, Computer Assisted Testing
Geographic Terms: Switzerland
DOI: 10.1037/xlm0001024
ISSN: 0278-7393
1939-1285
Abstract: Previous research indicates that long-term memory (LTM) may contribute to performance in working memory (WM) tasks. Across 3 experiments, we investigated the extent to which active maintenance in WM can be replaced by relying on information stored in episodic LTM, thereby freeing capacity for additional information in WM. First, participants encoded word pairs into LTM, and then completed a WM task, also involving word pairs. Crucially, the pairs presented in each WM trial comprised varying numbers of new pairs and the previously learned LTM pairs. Experiment 1 showed that recall performance in the WM task was unaffected when memory set size increased through the addition of LTM pairs, but that it deteriorated when set size increased through adding new pairs. In Experiment 2, we investigated the robustness of this effect, orthogonally manipulating the number of new and LTM pairs used in the WM task. When WM load was low, performance declined with the addition of LTM pairs but remained superior to performance with the matched set size comprising only new pairs. By contrast, when WM load was higher, adding LTM pairs did not affect performance. In Experiment 3, we found that the benefit of LTM representations arises from retrieving these during the WM test, leading them to suffer from typical interference effects. We conclude that individuals can outsource workload to LTM to optimize performance, and that the WM system negotiates the exchange of information between WM and LTM depending on the current memory load.
Abstractor: As Provided
Notes: https://osf.io/7d9aj
Entry Date: 2023
Accession Number: EJ1373265
Database: ERIC
Description
Abstract:Previous research indicates that long-term memory (LTM) may contribute to performance in working memory (WM) tasks. Across 3 experiments, we investigated the extent to which active maintenance in WM can be replaced by relying on information stored in episodic LTM, thereby freeing capacity for additional information in WM. First, participants encoded word pairs into LTM, and then completed a WM task, also involving word pairs. Crucially, the pairs presented in each WM trial comprised varying numbers of new pairs and the previously learned LTM pairs. Experiment 1 showed that recall performance in the WM task was unaffected when memory set size increased through the addition of LTM pairs, but that it deteriorated when set size increased through adding new pairs. In Experiment 2, we investigated the robustness of this effect, orthogonally manipulating the number of new and LTM pairs used in the WM task. When WM load was low, performance declined with the addition of LTM pairs but remained superior to performance with the matched set size comprising only new pairs. By contrast, when WM load was higher, adding LTM pairs did not affect performance. In Experiment 3, we found that the benefit of LTM representations arises from retrieving these during the WM test, leading them to suffer from typical interference effects. We conclude that individuals can outsource workload to LTM to optimize performance, and that the WM system negotiates the exchange of information between WM and LTM depending on the current memory load.
ISSN:0278-7393
1939-1285
DOI:10.1037/xlm0001024