Abstract
The speed with which information from vision is transformed into working memory (WM) representations that resist interference from ongoing perception and cognition is the subject of conflicting results. Using distinct paradigms, researchers have arrived at estimates of the consolidation time course ranging from 25 ms to 1 s – a range of more than an order of magnitude. However, comparisons of consolidation duration across very different estimation paradigms rely on the implicit assumption that WM consolidation speed is a stable, structural constraint of the WM system. The extremely large variation in WM consolidation speed estimates across measurement approaches motivated the current work’s goal of determining whether consolidation speed truly is a stable structural constraint of WM encoding, or instead might be under strategic control as suggested by some accounts. By manipulating the relative task priority of WM encoding and a subsequent sensorimotor decision in a dual-task paradigm, the current experiments demonstrate that the long duration of WM consolidation does not change as a result of task-specific strategies. These results allow comparison of WM consolidation across estimation approaches, are consistent with recent multi-phase WM consolidation models, and are consistent with consolidation duration being an inflexible structural limit.
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Notes
It is possible that prioritization could affect masked and unmasked conditions differentially. Thus, to be sensitive to this possibility (and to replicate the findings of Nieuwenstein and Wyble, 2014, as completely as possible), we include both masked and unmasked conditions in all experiments. We did not predict any such effect (i.e., any modulation of the key interactions for this study – SOA × presence of a dual task, or SOA × presence of a dual task × priority) and, to anticipate the results, no such modulation was found in any experiment. Thus, we do not focus on the masking manipulation in the remainder of this paper.
The only difference between Experiments 3 and 4, other than WM set size, is that Experiment 4 was performed online rather than in person. Thus, it could be that the online nature of Experiment 4, rather than the increased set size, drove the differences between Experiments 3 and 4. To rule out this alternative explanation, we replicated Experiment 3 online with an identical sample size. In doing so, we again observed evidence in favor of a SOA × T2-presence interaction (d’: BFIncl = 2.340, \({\eta}_p^2\) = 0.150; Accuracy: BFIncl = 9.994, \({\eta}_p^2\) = 0.236) and evidence against the inclusion of a SOA × T2 presence × priority interaction (d’: BFIncl = 0.109, \({\eta}_p^2\) = 0.012; Accuracy: BFIncl = .122, \({\eta}_p^2\) = 0.015). Furthermore, there was not an effect of priority (d’: BFIncl = 0.576, \({\eta}_p^2\) = 0.06; Accuracy: BFIncl = .555, \({\eta}_p^2\) = 0.050). Thus, the effects observed in Experiment 4 can be attributed to the increase in WM set size.
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Acknowledgements
This material is partially based upon work supported by the United States National Science Foundation under grant number 2127822.
The authors thank Harun Yoruk for helpful discussion related to the study; and Giang Le and Ryan Liu-Pham for technical assistance.
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All data have been made publicly available on the Open Science Framework and can be accessed via the Open Science Framework at the following link: https://osf.io/fpj45/. None of the experiments were preregistered.
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Carlos, B.J., Santacroce, L.A. & Tamber-Rosenau, B.J. The slow rate of working memory consolidation from vision is a structural limit. Atten Percept Psychophys 85, 2210–2225 (2023). https://doi.org/10.3758/s13414-023-02757-7
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DOI: https://doi.org/10.3758/s13414-023-02757-7