Working Memory Capacity and Fluid Intelligence: Maintenance and Disengagement
Abstract
Working memory capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working memory capacity is believed to facilitate reasoning through accurate maintenance of relevant information. In this article, we present a proposal reframing this issue, such that tests of working memory capacity and fluid intelligence are seen as measuring complementary processes that facilitate complex cognition. Respectively, these are the ability to maintain access to critical information and the ability to disengage from or block outdated information. In the realm of problem solving, high working memory capacity allows a person to represent and maintain a problem accurately and stably, so that hypothesis testing can be conducted. However, as hypotheses are disproven or become untenable, disengaging from outdated problem solving attempts becomes important so that new hypotheses can be generated and tested. From this perspective, the strong correlation between working memory capacity and fluid intelligence is due not to one ability having a causal influence on the other but to separate attention-demanding mental functions that can be contrary to one another but are organized around top-down processing goals.
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Shipstead et al. (2016) found that the negative correlation between fluid intelligence and n-back false alarms strengthened as lure position increased, indicating that lower fluid intelligence individuals were more likely to mistake far lures as targets.
“Shipstead et al. (2016) found that the negative correlation between fluid intelligence and n-back false alarms strengthened as the lure position increased, indicating that individuals with lower fluid intelligence were more likely to mistake far lures as targets.”
From Which “working memory” are we talking about? Complex span tasks versus N-back (2025) · cites this paper as Shipstead et al., 2016
Updating measures differ from working memory capacity measures mainly in how much they emphasize disengagement from outdated information.
“What distinguishes updating measures from working memory capacity measures is their relative emphasis on disengagement from outdated information”
From Which “working memory” are we talking about? Complex span tasks versus N-back (2025) · cites this paper as Shipstead et al., 2016
The disengagement hypothesis treats maintenance and disengagement as two critical factors linking executive functioning to fluid intelligence.
“This framework views maintenance and disengagement as two critical factors linking executive functioning to fluid intelligence (Burgoyne & Engle, 2020;Burgoyne et al., 2019;Hambrick & Altmann, 2015;Shipstead et al., 2016).”
From Which “working memory” are we talking about? Complex span tasks versus N-back (2025) · cites this paper as Shipstead et al., 2016
In n-back tasks, subjects must rapidly update working memory to disengage from outdated information in addition to maintaining n items.
“One challenge is that, in addition to having to maintain n items, subjects must also rapidly update the contents of working memory to disengage from outdated information (Oberauer, 2009;Shipstead et al., 2016;Szmalec et al., 2011)”
From Which “working memory” are we talking about? Complex span tasks versus N-back (2025) · cites this paper as Shipstead et al., 2016
Attention control supports both maintenance and disengagement.
“Attention control supports both maintenance and disengagement (Burgoyne & Engle, 2020;Shipstead et al., 2016).”
From Which “working memory” are we talking about? Complex span tasks versus N-back (2025) · cites this paper as Shipstead et al., 2016
Updating measures such as the n-back emphasize disengagement, and attention control serves to remove outdated items from focus.
“In contrast, updating measures (e.g., n-back) emphasize disengagement; the role of attention control is to remove outdated items from focus (Shipstead et al., 2016).”
From Which “working memory” are we talking about? Complex span tasks versus N-back (2025) · cites this paper as Shipstead et al., 2016
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Working Memory and Executive Attention: A Revisit
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Self-citationAttention Control: A Cornerstone of Higher-Order Cognition
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Why is working memory capacity related to matrix reasoning tasks?
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Self-citationThe Influence of Individual Differences in Cognitive Ability on Working Memory Training Gains
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Which “working memory” are we talking about? Complex span tasks versus N-back
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- Authors
- Shipstead, Z., Harrison, T. L., & Engle, R. W.
- Affiliations
- Arizona State University (US)
- Georgia Institute of Technology (US)
- Corresponding author
- Shipstead, Zach
- ORCID
- Engle, Randall W.
- Venue
- Perspectives on Psychological Science
- Publisher
- SAGE Publications
- Published
- 2016-11
- Volume
- 11
- Issue
- 6
- Pages
- 771-799
- ISSN
- 1745-6916 (ISSN-L)
- 1745-6924
- OpenAlex
- W2557282743
- Cited by
- 238
- References
- 165
- Citations by year
- 2026: 22 · 2025: 15 · 2024: 25 · 2023: 27 · 2022: 22 · 2021: 36 · 2020: 22 · 2019: 33 · 2018: 27 · 2017: 7 · 2015: 1 · 2014: 1
- FWCI
- 31.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Perspectives on Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Physical Sciences › Mathematics › Statistics and Probability › Cognitive and developmental aspects of mathematical skills
- Keywords
- working memory capacity, fluid intelligence, problem solving, hypothesis testing, disengagement, top-down processing, information maintenance, cognitive control
- MeSH terms
- Attention, Humans, Inhibition, Psychological, Intelligence, Memory, Short-Term, Models, Psychological, Problem Solving, Psychological Tests, Executive Function
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