Search

The limited capacity of working memory constrains how well we can think and act. Focused attention alleviates this limitation by prioritizing the most relevant mental content at a given time. Retro-cues tap into this ability by guiding attention to one working memory content, thereby improving memory speed and accuracy. So far, few attempts have been made to understand the retro-cue effect through well-established computational models, nor how their parameters track age-related changes and individual differences in focusing efficiency. The present study aims to close these gaps. We applied the drift-diffusion model to the data from a large sample of younger and older adults (total N = 346) that completed four retro-cue tasks. Diffusion modeling showed that retro-cues increased the quality of evidence accumulation, reduced the time taken for retrieval, and changed response conservativeness. Younger and older adults benefited from retro-cues in all tasks and parameters. Yet, age-related decline was observed in the retro-cue boost for evidence quality. Likewise, evidence quality was the only parameter capturing individual differences in focusing efficiency. Our results suggest that people differ in how well they can strengthen and protect a focused representation to boost evidence-quality accumulation, and this ability declines with aging.

Attention is a multifaceted mechanism operating on space, features, and memory. Previous studies reported both decline and preservation of attention in aging. Yet, it is unclear if healthy aging differentially affects attentional selection in these domains. To address these inconsistencies, we evaluated the ability to focus attention in a battery of 11 tasks in a large sample of younger and older adults (n = 172/174). We addressed if (1) aging effects are consistent across different attention tasks, and (2) if there is domain-specific or domain-general age-related decline in focused attention. Both younger and older adults benefited from focusing attention on space, features, and memory representations. Within the same domain, some tasks showed a decline, whereas others showed improvement with aging; and, on average, attentional benefits were similar across age groups. These results are inconsistent with the claim that aging is associated with either domain-specific or domain-general deficits in focused attention.

Behavioral change has been increasingly recognized as a means for combating climate change. However, being concerned about climate problems and knowing the importance of individual actions in mitigating them is not enough for greater adherence to a more sustainable lifestyle. Psychological barriers such as (1) finding the change unnecessary; (2) conflicting goals; (3) interpersonal relationships; (4) lack of knowledge; and (5) tokenism have been proposed as an explanation for the gap between environmental attitudes and actions. Yet, so far, this hypothesis has remained untested. This study aimed to assess if psychological barriers moderate the association between environmental attitudes and climate action. A sample of Portuguese individuals (N = 937) responded to a survey measuring climate change beliefs and environmental concerns as an index of environmental attitudes, a scale of self-reported frequency of environmental action, and finally, the dragons of inaction psychological barrier scale. Our participants revealed generally elevated positive environmental attitudes. These attitudes were positively and moderately related to greater self-reported frequency of environmental action in areas such as reusing materials, reduced consumption of animal products, water and energy saving, and airplane use, but not driving less. Critically, the association between attitudes and behavior was negatively moderated by psychological barriers for the reuse, food, and saving domains, but not for driving or flying. In conclusion, our results corroborate the assumption that psychological barriers can partly explain the attitude-behavior gap in the climate action domain.

One of the best-known demonstrations of long-term learning through repetition is the Hebb effect: Immediate recall of a memory list repeated amidst non-repeated lists improves steadily with repetitions. However, previous studies often failed to observe this effect for visuo-spatial arrays. Souza and Oberauer (2022) showed that the strongest determinant for producing learning was the difficulty of the test: Learning was consistently observed when participants recalled all items of a visuo-spatial array (difficult test) but not if only one item was recalled, or recognition procedures were used (less difficult tests). This suggests that long-term learning was promoted by increased testing demands over the short-term. Alternatively, it is possible that lower testing demands still lead to learning but prevented the application of what was learned. In four preregistered experiments (N = 981), we ruled out this alternative explanation: Changing the type of memory test mid-way through the experiment from less demanding (i.e., single item recall or recognition) to a more demanding test (i.e., full item recall) did not reveal hidden learning, and changing it from the more demanding to a less demanding test did not conceal learning. Mixing high and low demanding tests for non-repeated arrays, however, eventually produced Hebb learning even for the less demanding testing conditions. We propose that testing affects long-term learning in two ways: Expectations of the test difficulty influence how information is encoded into memory, and retrieval consolidates this information in memory.

Working memory performance is often assumed to benefit from different maintenance control strategies such as rehearsal, refreshing, elaboration, and grouping. In studies assessing strategy self-reports, some strategies were indeed associated with better recall. Nevertheless, experimental studies assessing the effect of instructing maintenance strategies compared to a no-instruction baseline lend no evidence for the effectiveness of these strategies for working memory. Explanations for this contradiction could be that instruction implementation engenders dual-task costs, or that strategy instructions reduce adaptive strategy switching. Across two experiments, we investigated the frequency and variability of strategy use with trial-wise self-reports in serial recall of word lists. Further, we examined potential instruction costs by comparing performance in trials with self-reported vs. instructed use of the same strategies. Self-reported strategy use varied from trial to trial, with elaboration and rehearsal being the most frequent. Self-reported elaboration was correlated with better performance than reading and rehearsal. For the most prevalent strategies – elaboration and rehearsal – there were no costs of instructed strategy-implementation. Our results speak against dual-task costs, and for an advantage of adaptively choosing one’s own strategy from trial to trial.

Many theories assume that actively maintaining information in working memory (WM) predicts its retention in episodic memory (EM), as revealed by the beneficial effects of more WM time. Here, we examined whether affording more time for intentional WM maintenance does indeed drive EM. Participants either intentionally or incidentally encoded sequences of four words presented during trials of simple span (short time) and complex and slow span (long time). Long time intervals entailed a pause of equivalent duration between the words that presented an arithmetic problem to read aloud and solve (complex span) or a blank screen (slow span). To ensure similar encoding of the words across the intentional and incidental encoding groups, participants silently decided whether each word was a living or nonliving thing via keypress (i.e., an animacy judgment; Experiment 1) or read the words aloud while pressing the spacebar (Experiment 2). A surprise delayed recall test at the end of the experiment assessed EM. Longer time in WM, particularly during slow span, improved retrieval from EM for both intentional and incidental encoding groups relative to short time, but for different reasons: modeling of the data indicated that longer intentional encoding increased binding memory (i.e., retrieval of the items’ positions in the trial; Experiments 1 and 2), whereas longer elaborative but incidental encoding increased item memory (i.e., memory of items irrespective of their bindings; Experiment 1). This suggests that time spent actively keeping information in WM is special for EM because WM is a system that maintains bindings.

Making accurate predictions of future memory performance (Judgements of Learning; JOLs) is a prerequisite for efficient learning. Since decades, those JOLs are assumed to be made inferentially, based on cues. This cue-utilization approach substituted the idea that JOLs are directly linked to memory quality. We criticize the reasons for the rejection of this memory-strength hypothesis because they ignore the existence of two different memory systems: working memory which holds representations immediately accessible, and long-term memory which is a more permanent store. Considering both memory systems, the current work revisited the memory-strength hypothesis: In Experiment 1, participants memorized sequences of two or four colored objects, then they provided JOLs for a long-term memory test, and performed a working memory test on the objects’ colors. After learning 200 objects, the long-term memory test on all studied objects followed. Sequence-length affected working memory, but not long-term memory performance. JOLs, however, were higher for sequences of two than four and correlated higher with working memory than long-term memory performance. Experiment 2 replicated the sequence-length effect on JOLs in the absence of a working memory test. Results of a sequence-eight condition revealed an increase in JOLs’ accuracy when the number of studied objects exceeded working memory span. Contrary to predominant theories, our findings suggest that JOLs are based on the quality of memory representations.

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.