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Drift-Diffusion Models (DDMs) are a widely-used class of models that assume an accumulation of evidence during a quick decision. These models are often used as measurement models to assess individual differences in cognitive processes, such as an individual's evidence accumulation rate and response caution. An additional underlying assumption of these models is that there is internal noise in the evidence accumulation process. However, fitting DDMs to experimental choice-response time data alone cannot yield estimates of an individual's evidence accumulation rate, caution, and internal noise at the same time. This is due to an intrinsic joint-unidentifiability of these parameters when fitting DDMs to behavioral data. We introduce methods of estimating these parameters at the same time with additional data types. The methods to estimate model parameters rely on Bayesian inference and simulation-based Bayesian inference. We show why these methods are useful without making strong assumptions.

The Hebb repetition effect shows improvement in serial recall of repeated lists compared to random nonrepeated lists. Previous research using simple span tasks found that the Hebb repetition effect is limited to constant uninterrupted lists, suggesting chunking as the mechanism of list learning. However, the Hebb repetition effect has been found in complex span tasks, which challenges the chunking explanation, as successive list items are separated by distractor processing, possibly interfering with the unified representations. We tested the possibility that Hebb repetition learning arises from chunking in simple span, but from position–item associations in complex span. In a series of five experiments, we found evidence that contradicts that hypothesis. Results show that (a) Hebb repetition learning in a complex span task can be transferred to a simple span task; (b) Hebb repetition learning from a complex span task cannot be transferred to a partially repeated simple span task; (c) partial repetition in a complex span task does not lead to learning; (d) Hebb repetition learning from a simple span task can be transferred to a complex span task; and (e) repeating the distractors in complex span has no impact on the Hebb repetition effect. These results suggest that the mechanism underlying the Hebb repetition effect in simple and complex span tasks is the same and points at the creation of chunks while excluding the distractors from the long-term memory representation.

The Hebb effect refers to the improvement in immediate memory performance on a repeated list compared to unrepeated lists. That is, participants create a long-term memory representation over repetitions, on which they can draw in working memory tests. These long-term memory representations are likely formed by chunk acquisition: The whole list becomes integrated into a single unified representation. Previous research suggests that the formation of such chunks is rather inflexible and only occurs when at least the beginning of the list repeats across trials. However, recent work has shown that repetition learning strongly depends on participants recognizing the repeated information. Hence, successful chunk formation may depend on the recognizability of the repeated part of a list, and not on its position in the list. Across six experiments, we compared these two alternatives. We tested immediate serial recall of eight-letter lists, some of which partially repeated across trials. We used different partial-repetition structures, such as repeating only the first half of a list, or only every second item. We manipulated the salience of the repeating structure by spatially grouping and coloring the lists according to the repetition structure. We found that chunk formation is more flexible than previously assumed: Participants learned contiguous repeated sequences regardless of their position within the list, as long as they were able to recognize the repeated structure. Even when the repeated sequence occurred at varying positions over repetitions, learning was preserved when the repeated sequence was made salient by the spatial grouping. These findings suggest that chunk formation requires recognition of which items constitute a repeating group, and demonstrate a close link between grouping of information in working memory, and chunk formation in long-term memory.

The Hebb repetition effect shows improvement in serial recall of repeated lists compared to random nonrepeated lists. Previous research using simple span tasks found that the Hebb repetition effect is limited to constant uninterrupted lists, suggesting chunking as the mechanism of list learning. However, the Hebb repetition effect has been found in complex span tasks, which challenges the chunking explanation, as successive list items are separated by distractor processing, possibly interfering with the unified representations. We tested the possibility that Hebb repetition learning arises from chunking in simple span, but from position-item associations in complex span. In a series of five experiments, we found evidence that contradicts that hypothesis. Results show that (a) Hebb repetition learning in a complex span task can be transferred to a simple span task; (b) Hebb repetition learning from a complex span task cannot be transferred to a partially repeated simple span task; (c) partial repetition in a complex span task does not lead to learning; (d) Hebb repetition learning from a simple span task can be transferred to a complex span task; and (e) repeating the distractors in complex span has no impact on the Hebb repetition effect. These results suggest that the mechanism underlying the Hebb repetition effect in simple and complex span tasks is the same and points at the creation of chunks while excluding the distractors from the long-term memory representation.

One of the best-known demonstrations of long-term learning through repetition is the Hebb effect: Immediate recall of a memory list repeated amidst nonrepeated lists improves steadily with repetitions. However, previous studies often failed to observe this effect for visuospatial 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 visuospatial 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 midway 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 nonrepeated 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.

Both the experimental and the psychometric investigation of the WM capacity limit depend critically on the assumption that performance in our tests of WM reflects that capacity limit to a good approximation. Most tasks to measure WM rely on testing memory after a short time during which participants are asked to maintain information in WM. In these tests, episodic long-term memory is likely to also lay down a trace of the memory set. Therefore, participants can draw on two sources of information when memory is tested, making it difficult to separate the contributions of WM and episodic LTM to the performance on immediate-memory tests. Here we use proactive interference to distinguish between these two sources of remembered information, building on the fact that episodic memory is vulnerable to proactive interference, whereas WM is protected against it. We use a release-from-PI paradigm to determine the extent to which commonly used WM tasks reflect contributions from episodic LTM. We focus on memory for serial order of verbal lists, but also include visual and spatial WM tasks. The results of five experiments demonstrate that although some tasks used to investigate WM are heavily contaminated by episodic LTM, other popular paradigms such as serial and probed recall, and the standard version of the continuous color-reproduction task, are not. Measuring proactive interference can help researchers determine the extent to which WM and episodic LTM contribute to performance in immediate-memory tasks.

Learning advances through repetition. A classic paradigm for studying this process is the Hebb repetition effect: Immediate serial recall performance improves for lists presented repeatedly as compared to nonrepeated lists. Learning in the Hebb paradigm has been described as a slow but continuous accumulation of long-term memory traces over repetitions [e.g., Page & Norris, Phil. Trans. R. Soc. B 364, 3737–3753 (2009)]. Furthermore, it has been argued that Hebb repetition learning requires no awareness of the repetition, thereby being an instance of implicit learning [e.g., Guérard et al., Mem. Cogn. 39, 1012–1022 (2011); McKelvie, J. Gen. Psychol. 114, 75–88 (1987)]. While these assumptions match the data from a group-level perspective, another picture emerges when analyzing data on the individual level. We used a Bayesian hierarchical mixture modeling approach to describe individual learning curves. In two preregistered experiments, using a visual and a verbal Hebb repetition task, we demonstrate that 1) individual learning curves show an abrupt onset followed by rapid growth, with a variable time for the onset of learning across individuals, and that 2) learning onset was preceded by, or coincided with, participants becoming aware of the repetition. These results imply that repetition learning is not implicit and that the appearance of a slow and gradual accumulation of knowledge is an artifact of averaging over individual learning curves.

Research on working memory (WM) has followed two largely independent traditions: One concerned with memory for sequentially presented lists of discrete items, and the other with short-term maintenance of simultaneously presented arrays of objects with simple, continuously varying features. Here we present a formal model of WM, the interference model (IM), that explains benchmark findings from both traditions: The shape of the error distribution from continuous reproduction of visual features, and how it is affected by memory set size; the effects of serial position for sequentially presented items, the effect of output position, and the intrusion of nontargets as a function of their distance from the target in space and in time. We apply the model to two experiments combining features of popular paradigms from both traditions: Lists of colors (Experiment 1) or of nonwords (Experiment 2) are presented sequentially and tested through selection of the target from a set of candidates, ordered by their similarity. The core assumptions of the IM are: Contents are encoded into WM through temporary bindings to contexts that serve as retrieval cues to access the contents. Bindings have limited precision on the context and the content dimension. A subset of the memory set-usually one item and its context-is maintained in a focus of attention with high precision. Successive events in an episode are encoded with decreasing strength, generating a primacy gradient. With each encoded event, automatic updating of WM reduces the strength of preceding memories, creating a recency gradient and output interference.

We appreciate the initiative to seek for ways to improve academic assessment by broadening the range of relevant research contributions and by considering a candidate’s scientific rigor. Evaluating a candidate's ability to contribute to science is a complex process that cannot be captured through one metric alone. While the proposed changes have some advantages, such as an increased focus on quality over quantity, the proposal's focus on adherence to open science practices is not sufficient, as it undervalues theory building and formal modelling: A narrow focus on open science conventions is neither a sufficient nor valid indicator for a “good scientist” and may even encourage researchers to choose easy, pre-registerable studies rather than engage in time-intensive theory building. Further, when in a first step only a minimum standard for following easily achievable open science goals is set, most applicants will soon pass this threshold. At this point, one may ask if the additional benefit of such a low bar outweighs the potential costs of such an endeavour. We conclude that a reformed assessment system should put at least equal emphasis on theory building and adherence to open science principles and should not completely disregard traditional performance metrices.

This work investigates how people make judgments about the content of their visual working memory (VWM). Some studies on long-term memory suggest that people base those metacognitive judgments on the outcome of a retrieval attempt. In contrast, Son and Metcalfe (2005) observed that people identify poorly remembered items immediately, presumably by the lack of familiarity for the retrieval cue. We tested these two hypotheses in the context of metacognition in VWM. In three experiments, we investigated participants’ response behavior in a color reproduction task with a hidden color wheel. With this procedure, participants must search for the intended response, starting from a random color. We assumed that instant awareness of the inability to retrieve an information would be reflected in selecting the first, random color, rather than search for a particular color in the wheel. Although participants provided a substantial number of low-confidence responses, results of an adapted mixture modeling analysis yielded little evidence for quick guesses. Rather, participants consistently searched for a color (even with unfamiliar retrieval cues in Experiment 2), and only quickly guessed when being cued with objects at test that were not previously presented (Experiment 3). We conclude that people usually engage in retrieval attempts for providing judgments about their VWM, even when information is poorly remembered.

Working memory (WM) is often tested through immediate serial recall of word lists. Performance in such tasks is negatively influenced by phonological similarity: People more often get the order of words wrong when they are phonologically similar to each other (e.g., cat, fat, mat). This phonological-similarity effect shows that phonology plays an important role for the representation of serial order in these tasks. By contrast, semantic similarity usually does not impact performance negatively. To resolve and understand this discrepancy, we tested the effects of phonological and semantic similarity for the retention of positional information in WM. Across six experiments (all Ns = 60 young adults), we manipulated between-item semantic and phonological similarity in tasks requiring participants to form and maintain new item-context bindings in WM. Participants were asked to retrieve items from their context, or the contexts from their item. For both retrieval directions, phonological similarity impaired WM for item-context bindings across all experiments. Semantic similarity did not. These results demonstrate that WM encodes phonological and semantic information differently. We propose a WM model accounting for semantic-similarity effects in WM, in which semantic knowledge supports WM through activated long-term memory.

The Hebb repetition effect on serial-recall task refers to the improvement in the accuracy of recall of a repeated list (e.g., repeated in every 3 trials) over random non-repeated lists. Previous research has shown that both temporal position and neighboring items need to be the same on each repetition list for the Hebb repetition effect to occur, suggesting chunking as one of its underlying mechanisms. Accordingly, one can expect absence of the Hebb repetition effect in a complex span task, given that the sequence is interrupted by distractors. Nevertheless, one study by Oberauer, Jones, and Lewandowsky (2015, Memory & Cognition, 43[6], 852–865) showed evidence of the Hebb repetition effect in a complex span task. Throughout four experiments, we confirmed the Hebb repetition effect in complex span tasks, even when we included distractors in both encoding and recall phases to avoid any resemblance to a simple span task and minimized the possibility of chunking. Results showed that the Hebb repetition effect was not affected by the distractors during encoding and recall. A transfer cycle analysis showed that the long-term knowledge acquired in the complex span task can be transferred to a simple span task. These findings provide the first insights on the mechanism behind the Hebb repetition effect in complex span tasks; it is at least partially based on the same mechanism that improves recall performance by repetition in simple span tasks.

People are able to prioritize more valuable information in working memory. The current study examined whether this value effect is due to the items of greater value being refreshed more than lower-value items during maintenance. To assess this possibility, we combined a probe value manipulation with a guided-refreshing procedure. Arrays of colored shapes were presented, and after a brief delay, participants reported the color of one randomly probed shape on a continuous color wheel. To manipulate probe value, one item was indicated as more valuable than the rest prior to encoding (i.e., worth more notional points), or all items were indicated as equally valuable. To guide refreshing, in some trials, two arrows were presented during maintenance, each arrow cueing the spatial location of one item. Participants were told to “think of” (i.e., refresh) the cued item. If value boosts are driven by attentional refreshing, cueing an item to be refreshed should enhance performance for items that are of low or equal value, but not items of high value, as these items would be refreshed regardless of the cue. This pattern of outcomes was observed, providing support for the hypothesis that attentional refreshing at least partially accounts for probe-value effects in working memory.

People are able to prioritize more valuable information in working memory. The current study examined whether this value effect is due to the items of greater value being refreshed more than lower-value items during maintenance. To assess this possibility, we combined a probe value manipulation with a guided-refreshing procedure. Arrays of colored shapes were presented, and after a brief delay, participants reported the color of one randomly probed shape on a continuous color wheel. To manipulate probe value, one item was indicated as more valuable than the rest prior to encoding (i.e., worth more notional points), or all items were indicated as equally valuable. To guide refreshing, in some trials, two arrows were presented during maintenance, each arrow cueing the spatial location of one item. Participants were told to “think of” (i.e., refresh) the cued item. If value boosts are driven by attentional refreshing, cueing an item to be refreshed should enhance performance for items that are of low or equal value, but not items of high value, as these items would be refreshed regardless of the cue. This pattern of outcomes was observed, providing support for the hypothesis that attentional refreshing at least partially accounts for probe-value effects in working memory.

We show that the intention to remember information substantially improves recall of that information when maintained in working memory (WM), whereas it does not have the same effect on maintenance in episodic long-term memory (LTM). In eight experiments, participants processed lists of words according to a semantic orienting task in three instruction conditions: to remember, to forget, or an incidental-memory baseline with no instruction. The first two experiments showed better memory for intentional remembering compared to incidental memory for a typical test of WM, but not for a typical test of episodic LTM. The subsequent six experiments determined which of three variables distinguishing typical WM and episodic-LTM tests-delay of test, list length, and proactive interference-are responsible for this difference. The intention to remember improved free-recall performance for short lists (close to the capacity limit of WM), most strongly when tested immediately, and only in the presence of proactive interference. This result supports a functional distinction between WM and episodic LTM: Whereas episodic LTM keeps a nonselective record of experiences for future use, WM holds selectively only the information relevant for the current goal. In addition, we found a beneficial effect of intentional remembering on memory for the list position of words, which was obtained for longer lists and regardless of the delay of testing, probably reflecting episodic LTM. The instruction to forget had no effect compared to the incidental baseline, questioning the assumption of a targeted forgetting process on memory.

Although storage in working memory (WM) can be tracked via measurements of ongoing neural activity, past work has shown that observers can maintain access to that information despite temporary interruptions of those neural patterns. This observation has been regarded as evidence for a neurally silent form of WM storage. Alternatively, however, unattended information could be retrieved from episodic long-term memory (eLTM) rather than being maintained in WM during the activity-silent period. Here, we tested between these possibilities by examining whether WM performance showed evidence of proactive interference (PI)-a hallmark of retrieval from eLTM-following such interruptions. Participants remembered the colors (Experiments 1-3) or locations (Experiment 4) of serially presented objects. We found PI for set sizes larger than 4, but not for smaller set sizes, suggesting that eLTM may have supported performance when WM capacity was exceeded. Critically, performance with small set sizes remained resistant to PI, even following prolonged interruptions by a challenging distractor task. Thus, we found evidence for PI-resistant memories that were maintained across likely interruptions of storage-related neural activity, an empirical pattern that implies activity-silent storage in WM.

Longer free time between presentation of verbal list items often leads to better immediate serial recall. The present series of three experiments demonstrates that this beneficial effect of time is more general than has been known: It is found for verbal items presented visually and auditorily (Experiments 1 and 2), and also when people engage in concurrent articulation during presentation, thereby preventing rehearsal (Experiment 3). The effect of time is to improve memory most strongly for the later part of the list, contrary to what is predicted from the assumption that time between items is used to bolster memory traces of already encoded items through rehearsal, refreshing, or elaboration. The data are compatible with a ballistic form of short-term consolidation, and with the assumption that encoding an item into working memory partially depletes a limited resource, which is replenished over time. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The present experiments support two conclusions about the capacity limit of working memory (WM). First, they provide evidence for the Binding Hypothesis, WM capacity is limited by interference between bindings but not items. Second, they show that episodic LTM contributes substantially to binding memory when the capacity of WM is stretched to the limit by larger set sizes. We tested immediate memory for sets of word-picture pairs. With increasing set size, memory for bindings declined more precipitously than memory for items, as predicted from the binding hypothesis. Yet, at higher set sizes performance was more stable than expected from a capacity limited memory, suggesting a contribution of episodic long-term memory (LTM) to circumvent the WM capacity limit. In support of that hypothesis, we show a double dissociation of contributions of WM and episodic LTM to binding memory: Performance at set sizes larger than 3 was specifically affected by proactive interference - but were immune to influences from a distractor-filled delay. In contrast, performance at set size 2 was unaffected by proactive interference but harmed by a distractor-filled delay.

The ability to store information in verbal working memory (WM) closely interacts with our linguistic knowledge. For instance, we can hold semantically related words (e.g., “cat, dog, bird”) better in our WM than unrelated ones (e.g., “desk, pillow, mouse”). This study investigates boundary conditions of the beneficial effect of semantic relatedness of words on immediate memory for lists. Independently varying the encoding and recall order for lists of related words, we unraveled several mechanistic explanations of the semantic relatedness effect. We first tested a semantic cueing mechanism, according to which the recall of an item facilitates the recall of other semantically related items. We next disentangled an interactive activation versus feature overlap account of semantic relatedness. Whereas the former predicts that the semantic relatedness effect emerges from the temporal co-activation of related items, the latter predicts that it emerges from the superposition of semantic features bound to similar contexts. Our results demonstrate that semantic relatedness affects WM performance at the encoding stage of WM processing, which rules out semantic cueing as a plausible mechanism. Further, the temporal order in which words are presented was the most important determinant of the semantic relatedness effect, in agreement with the interactive activation account. This study supports a model in which semantic relatedness supports WM through interactive activation occurring in semantic long-term memory.

How does the intent to remember or forget information affect working memory (WM)? To explore this question, in four experiments, we gauged the availability of the to-be-forgotten information directly. Participants remembered six words presented sequentially in separate frames. After each word offset, the frame turned either blue or orange, indicating a to-be-remembered or to-be-forgotten word, respectively. In all experiments, consistently poor recognition performance for to-be-forgotten words and facilitation of to-be-remembered words demonstrated that intent has a strong impact on WM. These directed-forgetting effects are remarkably robust: They can be observed when testing the to-be-forgotten words up to four times (Experiment 1, n = 341), for both item and binding memory (Experiment 3, n = 124), and even when information has to be maintained in WM up to 5 s until the memory cue is presented (Experiment 2 + 4, n = 302 + 321). Our study establishes a new method to jointly study the effects of intent on WM content for both relevant and irrelevant information and provides evidence for directed forgetting in WM. Our research suggests that a combination of two processes causes directed forgetting in WM: One process reduces memory strength of earlier memory representations as a function of subsequently encoded events. Another process rapidly encodes or boosts memory strength only when the person intends to remember that information.

Repeated exposure is assumed to promote long-term learning. This is demonstrated by the so-called "Hebb-effect": when short lists of verbal or spatial materials are presented sequentially for an immediate serial recall test, recall improves with list repetition. This repetition benefit, however, is not ubiquitous. Previous studies found little or no performance improvement for repetitions of visuospatial arrays (e.g., arrays of colored squares). Across eight experiments with college students and Prolific samples, we investigated which factors promote visuospatial learning by testing all combinations of variables distinguishing between visual-array tasks (brief + simultaneous presentation + a single recognition test) and tasks showing the Hebb effect (slow + sequential presentation + recall test probing all items). Participants profited from repetitions when all items were tested with a recall procedure, but not if the test consisted of recognition. Hence, the key to promote long-term learning is to recall all of the memorized information over the short-term.

Some theorists argue that working memory is limited to a discrete number of items and that additional items are not encoded at all. Adam et al. (2017) presented evidence supporting this hypothesis: Participants reproduced visual features of up to six items in a self-chosen order. After the third or fourth response, error distributions were indistinguishable from guessing. I present four experiments with young adults (each N = 24) reexamining this finding. Experiment 1 presented items slowly and sequentially. Experiment 2 presented them simultaneously but longer than in the experiments of Adam et al. Experiments 3 and 4 exactly replicated one original experiment of Adam et al. All four experiments failed to replicate the evidence for guessing-like error distributions. Modeling data from individuals revealed a mixture of some who do and others who do not produce guessing-like distributions. This heterogeneity increases the credibility of an alternative to the item-limit hypothesis: Some individuals decide to guess on hard trials even when they have weak information in memory.

Novelty-gated encoding is the assumption that events are encoded more strongly into memory when they are more novel in comparison to previously encoded events. It is a core assumption of the SOB model of serial recall (Farrell & Lewandowsky, 2002). We present three experiments testing some predictions from novelty-gated encoding. Experiment 1 shows that the probability of recalling the third item in a list correctly does not depend on whether it is preceded by phonologically similar or dissimilar items. Experiment 2 shows that in lists of items from three classes (nonwords, spatial locations, and abstract drawings) the probability of recalling an item does not depend on whether it is preceded by items from the same or another class. Experiment 3 used a complex-span paradigm varying the phonological similarity of words that are read aloud as distractors in between memory items. Contrary to a prediction from novelty-gated encoding, similar distractors did not impair memory more than dissimilar distractors. The results question the assumption of novelty-gated encoding in serial recall. We discuss alternative explanations for the phenomena that this assumption has previously helped to explain. The present evidence against novelty-gated encoding might point to boundary conditions for the role of prediction error in the acquisition of memories.

Despite over a century of research on intelligence, the cognitive processes underlying intelligent behavior are still unclear. In this review, we summarize empirical results investigating the contribution of cognitive processes associated with working memory capacity, processing speed, and executive processes to intelligence differences. Specifically, we (a) evaluate how cognitive processes associated with the three different cognitive domains have been measured, and (b) how these processes are related to individual differences in intelligence. Consistently, this review illustrates that isolating single cognitive processes using average performance in cognitive tasks is hardly possible. Instead, formal models that implement theories of cognitive processes underlying performance in different cognitive tasks may provide more adequate indicators of single cognitive processes. Therefore, we outlined which models for working memory capacity, processing speed, and executive processes may provide more specific insights into cognitive processes associated with individual differences in intelligence. Finally, we discuss implications of a process-oriented intelligence research using cognitive measurement models for psy- chometric theories of intelligence and argue that a model-based approach might overcome validity problems of traditional intelligence theories.

Mixed models are gaining popularity in psychology. For frequentist mixed models, previous research showed that excluding random slopes-differences between individuals in the direction and size of an effect-from a model when they are in the data can lead to a substantial increase in false-positive conclusions in null-hypothesis tests. Here, I demonstrated through five simulations that the same is true for Bayesian hypothesis testing with mixed models, which often yield Bayes factors reflecting very strong evidence for a mean effect on the population level even if there was no such effect. Including random slopes in the model largely eliminates the risk of strong false positives but reduces the chance of obtaining strong evidence for true effects. I recommend starting analysis by testing the support for random slopes in the data and removing them from the models only if there is clear evidence against them.

Previous research assumes that executive functions such as inhibition, shifting, and updating explain individual differences in cognitive abilities. Of these three executive functions, updating was previously found to relate most strongly to fluid intelligence. However, this relationship could be a methodological artifact: Measures of inhibition and shifting usually isolate the contribution of this executive function to performance by contrasting conditions with high and low demands on these processes, whereas updating is measured by overall accuracy in working memory tasks involving updating. This updating measure conflates updating-specific individual differences (e.g., removal of outdated information) with variance in working memory maintenance. Reanalyzing data (N = 111) from von Bastian et al. (2016), we separated updating-specific variance from working memory maintenance variance. Updating contributed only 15% to individual differences in performance in the updating tasks, and it correlated neither with fluid intelligence nor with independent working memory measures reflecting storage and processing or relational integration. In contrast, the working memory maintenance component of the updating task correlated with both abilities. These findings challenge the view that updating contributes to variance in higher cognitive abilities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Hebb repetition effect on serial-recall task refers to the improvement in the accuracy of recall of a repeated list (e.g., repeated in every 3 trials) over random non-repeated lists. Previous research has shown that both temporal position and neighboring items need to be the same on each repetition list for the Hebb repetition effect to occur, suggesting chunking as one of its underlying mechanisms. Accordingly, one can expect absence of the Hebb repetition effect in a complex span task, given that the sequence is interrupted by distractors. Nevertheless, one study by Oberauer, Jones, and Lewandowsky (2015, Memory & Cognition, 43[6], 852-865) showed evidence of the Hebb repetition effect in a complex span task. Throughout four experiments, we confirmed the Hebb repetition effect in complex span tasks, even when we included distractors in both encoding and recall phases to avoid any resemblance to a simple span task and minimized the possibility of chunking. Results showed that the Hebb repetition effect was not affected by the distractors during encoding and recall. A transfer cycle analysis showed that the long-term knowledge acquired in the complex span task can be transferred to a simple span task. These findings provide the first insights on the mechanism behind the Hebb repetition effect in complex span tasks; it is at least partially based on the same mechanism that improves recall performance by repetition in simple span tasks.

People are able to prioritize more valuable information in working memory. The current study examined whether this value effect is due to the items of greater value being refreshed more than lower-value items during maintenance. To assess this possibility, we combined a probe value manipulation with a guided-refreshing procedure. Arrays of colored shapes were presented, and after a brief delay, participants reported the color of one randomly probed shape on a continuous color wheel. To manipulate probe value, one item was indicated as more valuable than the rest prior to encoding (i.e., worth more notional points), or all items were indicated as equally valuable. To guide refreshing, in some trials, two arrows were presented during maintenance, each arrow cueing the spatial location of one item. Participants were told to "think of" (i.e., refresh) the cued item. If value boosts are driven by attentional refreshing, cueing an item to be refreshed should enhance performance for items that are of low or equal value, but not items of high value, as these items would be refreshed regardless of the cue. This pattern of outcomes was observed, providing support for the hypothesis that attentional refreshing at least partially accounts for probe value effects in working memory.

Most studies of visual-working memory employ one of two experimental paradigms: change-detection or continuous-stimulus reproduction. In this study, we extended the Interference Model (IM; Oberauer & Lin, 2017), which was designed for continuous reproduction, to the single-probe change-detection task. In continuous reproduction, participants occasionally report the non-target items instead of the target. The presence of non-target response is predicted by the Interference Model, which relies in part on the interference of non-target items to explain the set-size effect. By presenting a probe matching a non-target item, we can investigate the amount of interference from non-target items in change detection. As predicted by the Interference Model, we observed poorer performance in rejecting a probe matching a non-target item compared to a new probe (i.e., a cost due to intrusions from non-targets). We fitted the IM along with the Variable Precision, the Slot-Averaging, and the Neural-Population model to the data from two change-detection experiments. The models were equipped with a Bayesian decision rule based on the one used in Keshvari, van den Berg, and Ma (2013). The Interference Model and the Neural-Population model successfully predicted the set-size effect and the non-target intrusion cost, whereas the Variable Precision (VP) and Slot-Averaging (SA) models failed to predict the intrusion cost at all. Even with additional assumptions enabling VP and SA to produce intrusion costs, the IM still performed better than the competing models quantitatively.

When encoding task-relevant information in working memory (WM), we can use prior knowledge to facilitate task performance. For instance, when memorizing a phone number, we can benefit from recognizing some parts as known chunks (e.g., 911) and focus on memorizing the novel parts. Prior knowledge from long-term memory (LTM), however, can also proactively interfere with WM contents. Here, we show that WM selectively recruits information from LTM only when it is helpful, not when it would interfere. We used variants of the Hebb paradigm in which WM is tested through immediate serial recall of lists. Some lists were repeated frequently across trials, so they were acquired in LTM, as reflected in increasing serial-recall performance across repetitions. We compared interference conditions in which that LTM knowledge could interfere with holding another list in WM to a neutral condition in which that knowledge could be neither beneficial nor harmful. In Experiments 1-3, lists in the interference conditions shared their items with the learned lists but not their order. We observed no proactive interference. In Experiments 4 and 5, the interference lists' first three items overlapped exactly with the learned lists, and only the remaining items had a new order. This made LTM knowledge partially beneficial and partially harmful. Participants could use LTM flexibly to improve performance for the first part of the list without experiencing interference on the second half. LTM-mediated learning of the first part even boosted memory for the unknown second part. We conclude that there is a flexible gate controlling the flow of information from LTM and WM so that LTM knowledge is recruited only when helpful.

Is forgetting from working memory (WM) better explained by decay or interference? The answer to this question is the topic of an ongoing debate. Recently, a number of studies showed that performance in tests of visual WM declines with an increasing unfilled retention interval. This finding was interpreted as revealing decay. Alternatively, it can be explained by interference theories as an effect of temporal distinctiveness. According to decay theories, forgetting depends on the absolute time elapsed since the event to be retrieved. In contrast, temporal distinctiveness theories predict that memory depends on relative time, that is, the time since the to-be-retrieved event relative to the time since other, potentially interfering events. In the present study, we contrasted the effects of absolute time and relative time on forgetting from visual WM, using a continuous color recall task. To this end, we varied the retention interval and the inter-trial interval. The error in reporting the target color was a function of the ratio of the retention interval to the inter-trial interval, as predicted by temporal distinctiveness theories. Mixture modeling revealed that lower temporal distinctiveness produced a lower probability of reporting the target, but no changes in its precision in memory. These data challenge the role of decay in accounting for performance in tests of visual WM, and show that the relative spacing of events in time determines the degree of interference.

The Hebb repetition effect refers to the finding that immediate serial recall is improved over trials for memory lists that are surreptitiously repeated across trials, relative to new lists. We show in four experiments that the Hebb repetition effect is also observed with a complex-span task, in which encoding or retrieval of list items alternates with an unrelated processing task. The interruption of encoding or retrieval by the processing task did not reduce the size of the Hebb effect, demonstrating that incidental long-term learning forms integrated representations of lists, excluding the interleaved processing events. Contrary to the assumption that complex-span performance relies more on long-term memory than standard immediate serial recall (simple span), the Hebb effect was not larger in complex-span than in simple-span performance. The Hebb effect in complex span was also not modulated by the opportunity for refreshing list items, questioning a role of refreshing for the acquisition of the long-term memory representations underlying the effect.

Giving people more time to process information in working memory improves their performance on working memory tasks. It is often assumed that free time given after presentation of an item enables maintenance processes to counteract forgetting of this item, suggesting that time has a retroactive benefit. Two other hypotheses-short-term consolidation and temporal distinctiveness-entail a local effect of time on immediately preceding and following items. Here, we show instead a novel global and proactive benefit of time in working memory. In three serial-recall experiments (Ns = 21, 25, and 26 young adults, respectively), we varied the position and duration of the free time within a seven-item list of consonants. Experiment 1 showed that the effect is global and not local. Experiments 2a and 2b showed that increased interitem time benefited performance only for the subsequent items, implying a proactive benefit. This finding rules out maintenance processes, short-term consolidation, and temporal distinctiveness as explanations of the free-time benefit but is consistent with the proposal of a gradually recovering encoding resource.

In tests of working memory with verbal or spatial materials, repeating the same memory sets across trials leads to improved memory performance. This well-established "Hebb repetition effect" could not be shown for visual materials in previous research. The absence of the Hebb effect can be explained in two ways: Either persons fail to acquire a long-term memory representation of the repeated memory sets, or they acquire such long-term memory representations, but fail to use them during the working memory task. In two experiments (N$_{1}$ = 18 and N$_{2}$ = 30), we aimed to decide between these two possibilities by manipulating the long-term memory knowledge of some of the memory sets used in a change-detection task. Before the change-detection test, participants learned three arrays of colors to criterion. The subsequent change-detection test contained both previously learned and new color arrays. Change detection performance was better on previously learned compared with new arrays, showing that long-term memory is used in change detection.

There is a strong relationship between fluid intelligence and working memory capacity (WMC). Yet, the cognitive mechanisms underlying this relationship remain elusive. The capacity hypothesis states that this relationship is due to limitations in the amount of information that can be stored and held active in working memory. Previous research aimed at testing the capacity hypothesis assumed that it implies stronger relationships of intelligence test performance with WMC for test items with higher capacity demands. The present article addresses this assumption through simulations of three theoretical models implementing the capacity hypothesis while systematically varying different psychometric variables. The results show that almost any relation between the capacity demands of items and their correlation with WMC can be obtained. Therefore, the assumption made by previous studies does not hold: The capacity hypothesis does not imply stronger correlations of WMC and intelligence test items with higher capacity demands. Items varying in capacity demands cannot be used to test the causality of WMC (or any other latent variable) for fluid intelligence.

Free time to attend to and process information in working memory is key in promoting immediate and delayed retention. One candidate process to cause this benefit is elaboration. We conducted three experiments with young adults – two of which included older adults – to investigate whether free time is used for elaboration, and whether elaboration causes the free-time benefit. Participants remembered lists of nouns, interleaved with short or long free-time intervals, or with filler words connecting all the nouns into a meaningful sentence to assist elaboration. For young adults, assisted elaboration through sentences, and the additional instruction to form a mental image, benefited performance in a working-memory test as much as longer free time, but not more. In contrast, for a delayed test of long-term memory, the benefits of sentence elaboration exceeded those of longer free time. Older adults did not benefit from assisted elaborations in the delayed test, providing further evidence that the long-term memory deficit of older adults arises at least in part from a deficit in elaboration. This elaboration deficit is not driven by a deficit in generating richer representations.

There is a broad agreement that psychology is facing a replication crisis. Even some seemingly well-established findings have failed to replicate. Numerous causes of the crisis have been identified, such as underpowered studies, publication bias, imprecise theories, and inadequate statistical procedures. The replication crisis is real, but it is less clear how it should be resolved. Here we examine potential solutions by modeling a scientific community under various different replication regimes. In one regime, all findings are replicated before publication to guard against subsequent replication failures. In an alternative regime, individual studies are published and are replicated after publication, but only if they attract the community's interest. We find that the publication of potentially non-replicable studies minimizes cost and maximizes efficiency of knowledge gain for the scientific community under a variety of assumptions. Provided it is properly managed, our findings suggest that low replicability can support robust and efficient science.

The processing of ordinally organized information is a characteristic of both serial-order working memory and numerical cognition. Serial positions of items presented within a list follow an ordinal organization when stored in working memory, whereas numbers are based on an ordinal structure stored in long-term memory. We tested the hypothesis that long-term numerical ordinal representations support the coding of temporary serial position information in working memory. In Experiment 1, learned word-number associations appeared to have a negative instead of a positive impact on immediate serial recall performance relative to control conditions. Experiments 2 showed that this effect was due to a stronger opportunity for learning associations of words to serial positions in the control lists as compared to the experimental lists. Experiment 3 showed that when controlling for these positional learning effects, there was no reliable effect of learned word-number associations on immediate serial recall performance. This study indicates that numerical codes do not play a major role in coding serial position information in working tasks. At the same time, the robust item-position learning effects demonstrate a contribution of long-term item-position associations to immediate memory for order. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

There is a strong relationship between fluid intelligence and working memory capacity (WMC). Yet, the cognitive mechanisms underlying this relationship remain elusive. The capacity hypothesis states that this relationship is due to limitations in the amount of information that can be stored and held active in working memory. Previous research aimed at testing the capacity hypothesis assumed that it implies stronger relationships of intelligence test performance with WMC for test items with higher capacity demands. The present article addresses this assumption through simulations of three theoretical models implementing the capacity hypothesis while systematically varying different psychometric variables. The results show that almost any relation between items’ capacity demands and their correlation with WMC can be obtained. Therefore, the assumption made by previous studies does not hold: The capacity hypothesis does not imply stronger correlations of WMC and intelligence test items with higher capacity demands. Items varying in capacity demands cannot be used to test the causality of WMC (or any other latent variable) for fluid intelligence.

Refreshing – briefly attending to an item in working memory – has been proposed as a domain-general maintenance process. According the time-based resource-sharing (TBRS) theory, people refresh the contents of working memory sequentially at high speed. We measured the speed of refreshing by asking participants to sequentially refresh a small set of items in sync with a metronome, and to adjust the metronome to the fastest speed at which they could refresh. Refreshing speeds converged on about 0.2 s per item for several verbal and visual materials. This time was shorter than the speed of articulatory rehearsal measured with the same method, and – in contrast to rehearsal – did not depend on word length. We sought evidence for people refreshing in sync with the metronome by presenting recognition probes at unpredictable times. We expected that probes matching the just-refreshed item should be recognized faster and more accurately than probes matching other items. This was not the case. A parallel experiment with overt articulatory rehearsal showed poor synchronization of rehearsal with the metronome, suggesting by analogy that refreshing was equally out of sync. The results support the assumption that people can attend sequential to items in working memory, and monitor this process. This refreshing process is probably faster than rehearsal, but it is unlikely to be possible as fast as the refreshing process assumed in the TBRS theory.

Human attention is subject to fluctuations. Mind-wandering (MW) - attending to thoughts unrelated to the current task demands - is considered a ubiquitous experience. According to the Control Failure x Concerns view (McVay & Kane, 2010), MW is curbed by executive control, and task-irrelevant thoughts enter consciousness due to attentional control lapses. The generation of off-task thoughts is assumed to increase with higher number of personal concerns. Challenging this view, older adults report less MW than younger adults. Here, we addressed the hypothesis that older adults report less MW due to a lower ability to notice attention lapses and to appraise their current on-task focus. In an age-comparative study (N = 40 younger and N = 44 older adults) using a battery of three tasks spanning working memory, reading comprehension, and sustained attention, we assessed the correlation between the degree of self-reported on-task focus and task performance on a trial-by-trial basis. Younger and older adults' degree of on-task attention measured through thought probes was correlated equally strongly with performance across trials in all tasks, indicating preserved ability to monitor attentional fluctuations in healthy aging. Self-reported current concerns' number and importance did not differ across age, and they did not predict self-reported attention across tasks. Our study shows that lower rates of MW in aging do not reflect lower validity of older adults' attentional appraisal or lower levels of current concerns.

The process of spontaneous refreshing plays a central role in current models of working memory but is yet to be observed directly. In a recent study, Rey, Versace, and Plancher (2018) introduced a novel approach to investigate the mechanisms underlying refreshing: They presented tones previously associated with a visual mask during the free time of a complex span task and found that this impaired memory, presumably because reactivation of the masks disrupts refreshing. Here, we aimed to replicate their finding under more controlled settings with more observations per participant. We failed to replicate the previous findings, thereby questioning the robustness of the original effect.

It is usually assumed that articulatory rehearsal improves verbal working memory. Complex span is the most used paradigm to assess working memory functioning; yet, we still lack knowledge about how participants rehearse in this task, and whether these rehearsals are beneficial. In Experiment 1, we investigated the patterns of naturally occurring overt rehearsals in a complex span task requiring processing of a non-verbal distractor task. For comparison, another group of participants completed a matched simple span task with an unfilled delay in between the memoranda. Time permitting, participants rehearsed the memory list in forward serial order, a strategy known as cumulative rehearsal. The degree of cumulative rehearsal was correlated with recall accuracy in both span tasks. Rehearsal frequency was, however, reduced in complex span compared to simple span. To assess the causal role of rehearsal in complex span, we trained a group of participants in a cumulative rehearsal strategy in Experiment 2. This instruction substantially increased the prevalence of cumulative rehearsals compared to a control group. However, the increase in cumulative rehearsal did not translate into an increase in recall accuracy. Our results provide further evidence that rehearsal does not benefit working memory performance.

Some issues that have been settled by the scientific community, such as evolution, the effectiveness of vaccinations, and the role of CO$_{2}$ emissions in climate change, continue to be rejected by segments of the public. This rejection is typically driven by people's worldviews, and to date most research has found that conservatives are uniformly more likely to reject scientific findings than liberals across a number of domains. We report a large (N > 1,000) preregistered study that addresses two questions: First, can we find science denial on the left? Endorsement of pseudoscientific complementary and alternative medicines (CAM) has been anecdotally cited as being more consonant with liberals than conservatives. Against this claim, we found more support for CAM among conservatives than liberals. Second, we asked how liberals and conservatives resolve dilemmas in which an issue triggers two opposing facets of their worldviews. We probed attitudes on gender equality and the evolution of sex differences-two constructs that may create conflicts for liberals (who endorse evolution but also equality) and conservatives (who endorse gender differences but are sceptical of evolution). We find that many conservatives reject both gender equality and evolution of sex differences, and instead embrace "naturally occurring" gender differences. Many liberals, by contrast, reject evolved gender differences, as well as naturally occurring gender differences, while nonetheless strongly endorsing evolution.

Some issues that have been settled by the scientific community, such as evolution, the effectiveness of vaccinations, and the role of CO2 emissions in climate change, continue to be rejected by segments of the public. This rejection is typically driven by people's worldviews, and to date most research has found that conservatives are uniformly more likely to reject scientific findings than liberals across a number of domains. We report a large (N>1,000) preregistered study that addresses two questions: First, can we find science denial on the left?Endorsement of pseudoscientific complementary and alternative medicines (CAM) has been anecdotally cited as being more consonant with liberals than conservatives. Against this claim, we found more support for CAM among conservatives than liberals. Second, we asked how liberals and conservatives resolve dilemmas in which an issue triggers two opposing facets of their worldviews. We probed attitudes on gender equality and the evolution of sex differences---two constructs that may create conflicts for liberals (who endorse evolution but also equality) and conservatives (who endorse gender differences but are sceptical of evolution). We find that many conservatives reject both gender equality and evolution of sex differences, and instead embrace ``naturally occurring'' gender differences. Many liberals, by contrast, reject evolved gender differences, as well as naturally occurring gender differences, while nonetheless strongly endorsing evolution.

The process of spontaneous refreshing plays a central role in current models of working memory but is yet to be observed directly. In a recent study, Rey and colleagues (Rey, Versace, & Plancher, 2018) introduced a novel approach to investigate the mechanisms underlying refreshing: They presented tones previously associated with a visual mask during the free time of a complex span task, and found that this impaired memory, presumably because reactivation of the masks disrupts refreshing. Here we aimed to replicate their finding under more controlled settings with more observations per participant. We failed to replicate the previous findings, thereby questioning the robustness of the original effect.

This is a brief reply to the commentaries by Adam and deBettencourt (2019); Allen (2019); Kiyonaga (2019); Schneider (2019); and Van der Stigchel and Olivers (2019), focusing on four topics: (1) I defend the idea that attention need not be characterized as a limited resource. (2) I explain how I conceptualize the role of WM in cognitive control, and how recruitment of sensory processing networks contributes to control but not maintenance. (3) I discuss different ways in which information can be selectively prioritized during or after being encoded into WM, and the different consequences of these processes. (4) I argue that sustained attention to a task can be understood as the mind's ability to prioritize that task over task-unrelated representations.

A worrying number of psychological findings are not replicable. Diagnoses of the causes of this "replication crisis," and recommendations to address it, have nearly exclusively focused on methods of data collection, analysis, and reporting. We argue that a further cause of poor replicability is the often weak logical link between theories and their empirical tests. We propose a distinction between discovery-oriented and theory-testing research. In discovery-oriented research, theories do not strongly imply hypotheses by which they can be tested, but rather define a search space for the discovery of effects that would support them. Failures to find these effects do not question the theory. This endeavor necessarily engenders a high risk of Type I errors-that is, publication of findings that will not replicate. Theory-testing research, by contrast, relies on theories that strongly imply hypotheses, such that disconfirmation of the hypothesis provides evidence against the theory. Theory-testing research engenders a smaller risk of Type I errors. A strong link between theories and hypotheses is best achieved by formalizing theories as computational models. We critically revisit recommendations for addressing the "replication crisis," including the proposal to distinguish exploratory from confirmatory research, and the preregistration of hypotheses and analysis plans.

There is broad agreement that working memory is closely related to attention. This article delineates several theoretical options for conceptualizing this link, and evaluates their viability in light of their theoretical implications and the empirical support they received. A first divide exists between the concept of attention as a limited resource, and the concept of attention as selective information processing. Theories conceptualizing attention as a resource assume that this resource is responsible for the limited capacity of working memory. Three versions of this idea have been proposed: Attention as a resource for storage and processing, a shared resource for perceptual attention and memory maintenance, and a resource for the control of attention. The first of these three is empirically well supported, but the other two are not. By contrast, when attention is understood as a selection mechanism, it is usually not invoked to explain the capacity limit of working memory - rather, researchers ask how different forms of attention interact with working memory, in two areas. The first pertains to attentional selection of the contents of working memory, controlled by mechanisms of filtering out irrelevant stimuli, and removing no-longer relevant representations from working memory. Within working memory contents, a single item is often selected into the focus of attention for processing. The second area pertains to the role of working memory in cognitive control. Working memory contributes to controlling perceptual attention - by holding templates for targets of perceptual selection - and controlling action - by holding task sets to implement our current goals.