There has been considerable controversy in recent years as to whether information held in working memory (WM) is rapidly forgotten or automatically transferred to long-term memory (LTM). Although visual WM capacity is very limited, we appear able to store a virtually infinite amount of information in visual LTM. Still, LTM retrieval often fails. Some view visual WM as a mental sketchpad that is wiped clean when new information enters, but not a consistent precursor of LTM. Others view the WM and LTM systems as inherently linked. Distinguishing between these possibilities has been difficult, as attempts to directly manipulate the active holding of information in visual WM has typically introduced various confounds. Here, we capitalized on the WM system's capacity limitation to control the likelihood that visual information was actively held in WM. Our young-adult participants (N = 103) performed a WM task with unique everyday items, presented in groups of two, four, six, or eight items. Presentation time was adjusted according to the number of items. Subsequently, we tested participants' LTM for items from the WM task. LTM was better for items presented originally within smaller WM set sizes, indicating that WM limitations contribute to subsequent LTM failures, and that holding items in WM enhances LTM encoding. Our results suggest that a limit in WM capacity contributes to an LTM encoding bottleneck for trial-unique familiar objects, with a relatively large effect size.
The decline of working memory (WM) is a common feature of general cognitive decline, and visual and verbal WM capacity appear to decline at different rates with age. Visual material may be remembered via verbal codes or visual traces, or both. Souza and Skóra, Cognition, 166, 277–297 (2017) found that labeling boosted memory in younger adults by activating categorical visual long-term memory (LTM) knowledge. Here, we replicated this and tested whether it held in healthy older adults. We compared performance in silence, under instructed overt labeling (participants were asked to say color names out loud), and articulatory suppression (repeating irrelevant syllables to prevent labeling) in the delayed estimation paradigm. Overt labeling improved memory performance in both age groups. However, comparing the effect of overt labeling and suppression on the number of coarse, categorical representations in the two age groups suggested that older adults used verbal labels subvocally more than younger adults, when performing the task in silence. Older adults also appeared to benefit from labels differently than younger adults. In younger adults labeling appeared to improve visual, continuous memory, suggesting that labels activated visual LTM representations. However, for older adults, labels did not appear to enhance visual, continuous representations, but instead boosted memory via additional verbal (categorical) memory traces. These results challenged the assumption that visual memory paradigms measure the same cognitive ability in younger and older adults, and highlighted the importance of controlling differences in age-related strategic preferences in visual memory tasks.
We explored the causal role of individual and age-related differences in working memory (WM) capacity in long-term memory (LTM) retrieval. Our sample of 160 participants included 120 children (6-13-years old) and 40 young adults (18-24 years). Participants performed a WM task with images of unique everyday items, presented at varying set sizes. Subsequently, we tested participants' LTM for items from the WM task. Using these measures, we estimated the ratio at which items successfully held in WM were recognized in LTM. While WM and LTM generally improved with age, the ability to transfer information from WM to LTM appeared consistent between age groups. Moreover, individual differences in WM capacity appeared to predict LTM encoding. Overall, these results suggested that LTM performance was constrained by experimental, individual, and age-related WM limitations. We discuss the theoretical and practical implications of this WM-to-LTM bottleneck.
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