Refreshing and elaboration are cognitive processes assumed to underlie verbal working-memory maintenance and assumed to support long-term memory formation. Whereas refreshing refers to the attentional focussing on representations, elaboration refers to linking representations in working memory into existing semantic networks. We measured the impact of instructed refreshing and elaboration on working and long-term memory separately, and investigated to what extent both processes are distinct in their contributions to working as well as long-term memory. Compared with a no-processing baseline, immediate memory was improved by repeating the items, but not by refreshing them. There was no credible effect of elaboration on working memory, except when items were repeated at the same time. Long-term memory benefited from elaboration, but not from refreshing the words. The results replicate the long-term memory benefit for elaboration, but do not support its beneficial role for working memory. Further, refreshing preserves immediate memory, but does not improve it beyond the level achieved without any processing.

Attentional control as an ability to regulate information processing during goal-directed behavior is critical to many theories of human cognition and thought to predict a large range of everyday behaviors. However, in recent years, failures to reliably assess individual differences in attentional control have sparked a debate concerning whether attentional control, as currently conceptualized and assessed, can be regarded as a valid psychometric construct. In this consensus paper, we summarize the current debate from theoretical, methodological, and analytical perspectives. First, we propose a consensus-based definition of attentional control and the cognitive mechanisms that potentially contribute to individual differences in attentional control. Next, guided by the findings of an in-depth literature survey, we discuss the psychometric considerations that are critical when assessing attentional control. We then provide suggestions for recent methodological and analytical approaches that can alleviate the most common concerns. We conclude that, to truly advance our understanding of the construct of attentional control, we must develop a theory-driven and empirically supported consensus on how we define, operationalize, and assess attentional control. This consensus paper presents a first step to achieve this goal; a shift toward transparent reporting, sharing of materials and data, and cross-laboratory efforts will further accelerate progress.

Maintenance of information in working memory (WM) is assumed to rely on refreshing and elaboration, but clear mechanistic descriptions of these cognitive processes are lacking, and it is unclear whether they are simply two labels for the same process. This fMRI study investigated the extent to which refreshing, elaboration, and repeating of items in WM are distinct neural processes with dissociable behavioral outcomes in WM and long-term memory (LTM). Multivariate pattern analyses of fMRI data revealed differentiable neural signatures for these processes, which we also replicated in an independent sample of older adults. In some cases, the degree of neural separation within an individual predicted their memory performance. Elaboration improved LTM, but not WM, and this benefit increased as its neural signature became more distinct from repetition. Refreshing had no impact on LTM, but did improve WM, although the neural discrimination of this process was not predictive of the degree of improvement. These results demonstrate that refreshing and elaboration are separate processes that differently contribute to memory performance.

We thank Jessica Grub, Gary Hoppeler and Danielle Pessach for helping with data collection. The data and the analysis scripts can be accessed on the Open Science Framework

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.

No abstract

Adaptive behavior in daily life often requires the ability to acquire and represent sequential contingencies between actions and the associated outcomes. Although accumulating evidence implicates the role of dorsolateral prefrontal cortex (dlPFC) in complex value-based learning and decision-making, direct evidence for involvements of this region in integrating information across sequential decision states is still scarce. Using a 3-stage deterministic Markov decision task, here we applied offline, inhibitory low-frequency 1-Hz repetitive transcranial magnetic stimulation (rTMS) over the left dlPFC in young male adults (n = 31, mean age = 23.8 years, SD = 2.5 years) in a within-subject cross-over design to study the roles of this region in influencing value-based sequential decision-making. In two separate sessions, each participant received 1-Hz rTMS stimulation either over the left dlPFC or over the vertex. The results showed that transiently inhibiting the left dlPFC impaired choice accuracy, particularly in situations in which the acquisition of sequential transitions between decision states and temporally lagged action-outcome contingencies played a greater role. Estimating parameters of a diffusion model from behavioral choices, we found that the diffusion drift rate, which reflects the efficiency of information integration, was attenuated by the stimulation. Moreover, the effects of rTMS interacted with session: individuals who could not efficiently integrate information across sequential states in the first session due to disrupted dlPFC function also could not catch up in performance during the second session with those individuals who could learn sequential transitions with intact dlPFC function in the first session. Taken together, our findings suggest that the left dlPFC is crucially involved in the acquisition of complex sequential relations and in the potential of such learning.

Priority-based allocation of attentional resources has shown robust effects in working memory (WM) with both cue-based and reward-based prioritization. However, direct comparisons between these effects in WM are needed. Additionally, the consequences of WM prioritization for remembering in the long term remain unclear for both prioritization procedures. Here, we tested and compared the immediate and long-term memory (LTM) effects of cue-based versus reward-based retrospective prioritization of WM content. Participants encoded four memory items and were then indicated to prioritize one of the items through the presentation of either a retro-cue or a reward pattern. We then tested their immediate and delayed memory. The results of the first experiment showed better memory for prioritized than for unprioritized information in WM and LTM, but the WM effect was driven solely by the retro-cue, making it difficult to interpret any reward-based effects in LTM. In the second experiment, using a more explicit and meaningful reward-based manipulation, the results showed a prioritization benefit in WM for both prioritization procedures. In LTM, however, the prioritization effect was predominantly driven by the retro-cue manipulation. Taken together, we found that (1) the way in which attention is directed in WM impacts the size of the prioritization benefit in WM, (2) WM prioritization generally results in a prioritization effect in LTM, and (3) that the effect in LTM is more robust for cue-based prioritization. Exploratory analyses indicated that the LTM effect of cue-based prioritization reflected a cost in performance for noncued items rather than a benefit for cued items.