Working memory (WM) is the set of mental processes holding limited information in a temporarily accessible state in service of cognition. We provide a theoretical framework to understand the relation between WM and aptitude measures. The WM measures that have yielded high correlations with aptitudes include separate storage and processing task components, on the assumption that WM involves both storage and processing. We argue that the critical aspect of successful WM measures is that rehearsal and grouping processes are prevented, allowing a clearer estimate of how many separate chunks of information the focus of attention circumscribes at once. Storage-and-processing tasks correlate with aptitudes, according to this view, largely because the processing task prevents rehearsal and grouping of items to be recalled. In a developmental study, we document that several scope-of-attention measures that do not include a separate processing component, but nevertheless prevent efficient rehearsal or grouping, also correlate well with aptitudes and with storage-andprocessing measures. So does digit span in children too young to rehearse. Keywordsworking memory; short-term memory; individual differences; variation in working memory; cholastic abilities; intellectual abilities; attention; capacity; storage capacity Baddeley and Hitch (1974) highlighted a key theoretical construct, working memory (WM), which can be described generally as the set of mechanisms capable of retaining a small amount of information in an active state for use in ongoing cognitive tasks (though it now means Research on WM suggests that the measures used most often to examine individual differences have both strengths and weaknesses. A main type of strength is their strong correlation with intellectual aptitude tests, and a main type of weakness is the difficulty encountered in analyzing and interpreting WM test results. This difficulty stems largely from the reliance on dual tasks in the measurement of WM capacity (which include separate storage and processing task components). We will argue that the research literature provides hints that the strengths can be retained without using storage-and-processing measures. We will offer a theoretical framework for doing so, and for measuring WM in a more meaningful way than is found with current measurement practices. The theoretical framework is based on the notion of an adjustable attentional focus and on measures of the storage capacity of attention or its scope. The predictions tested in the present article pertain to the scope of attention, whereas the adjustable nature of the focus allows consistency with other highly relevant research (e.g., Kane, Bleckley, Conway, & Engle, 2001).We do not judge the success of this endeavor by whether storage-and-processing measures or the proposed alternative, scope-of-attention measures, pick up more variance in aptitude tasks.Rather, success will be judged by whether the variance that is picked up contributes to our understanding of the processes underlyi...

Visual working memory is often modeled as having a fixed number of slots. We test this model by assessing the receiver operating characteristics (ROC) of participants in a visual-working-memory change-detection task. ROC plots yielded straight lines with a slope of 1.0, a tell-tale characteristic of all-or-none mnemonic representations. Formal model assessment yielded evidence highly consistent with a discrete fixed-capacity model of working memory for this task.working memory ͉ capacity ͉ mathematical models of memory ͉ short-term memory T he study of the nature and capacity of visual working memory (WM) is both timely (1) and controversial (2, 3). A popular conceptualization is that visual WM consists of a fixed number of discrete slots in which items or chunks are temporarily held (2, 4, 5). Nonetheless, there are dissenting viewpoints in which the discreteness is taken as, at most, a convenient oversimplification (6, 7). In this article, we provide a rigorous test of the fixed-capacity model for a visual WM task. Herein, we apply this test to items that differ in color, although the test is suitable to examine the generality of capacity limits across various materials.We used a common version (8-15) of the task popularized by Luck and Vogel (4, 16) (see Fig. 1A). At study, participants are presented with an array of colored squares. At test, a single square is presented; this square is either the same color as the corresponding square in the study array (a "same trial") or a novel color (a "change trial"). Participants simply decide whether the test square is the same as or different from the corresponding studied square. In this task, where the color of each square is unique and the colors are well separated, capacity is the number of squares (objects) that may be held in visual WM. This object-based view of capacity is supported by previous research (4), in which performance does not vary with the number of manipulated features per object.Previous demonstrations of fixed capacity have relied on plotting capacity estimates as a function of the number of to-be-remembered items. Fixed capacity is claimed because capacity estimates tend to asymptote at three to four items for array sizes of four to six items. This approach, however, is not the most rigorous for this model. There are three weaknesses in previous demonstrations: (i) The asymptote of the capacity estimated may be mimicked by models without recourse to fixed capacity; (ii) previous demonstrations are made with aggregate data, and an asymptote in the group aggregate does not necessarily imply asymptotes in all or any individuals; and (iii) the stability of these asymptotes has not been formally assessed. These weaknesses motivate a more constrained test, to be presented subsequently.The Fixed-Capacity Almost-Ideal Observer Model. We define the fixed-capacity ideal observer as one who maximizes the probability of a correct response given the constraint that visual WM is discrete and limited in the number of items that may be held. Here, we derive th...

Any mature field of research in psychology-such as short-term/working memory-is characterized by a wealth of empirical findings. It is currently unrealistic to expect a theory to explain them all; theorists must satisfice with explaining a subset of findings. The aim of the present article is to make the choice of that subset less arbitrary and idiosyncratic than is current practice. We propose criteria for identifying benchmark findings that every theory in a field should be able to explain: Benchmarks should be reproducible, generalize across materials and methodological variations, and be theoretically informative. We propose a set of benchmarks for theories and computational models of short-term and working memory. The benchmarks are described in as theory-neutral a way as possible, so that they can serve as empirical common ground for competing theoretical approaches. Benchmarks are rated on three levels according to their priority for explanation. Selection and ratings of the benchmarks is based on consensus among the authors, who jointly represent a broad range of theoretical perspectives on working memory, and they are supported by a survey among other experts on working memory. The article is accompanied by a web page providing an open forum for discussion and for submitting proposals for new benchmarks; and a repository for reference data sets for each benchmark. (PsycINFO Database Record

Although the measurement of working memory capacity is crucial to understanding working memory and its interaction with other cognitive faculties, there are inconsistencies in the literature on how to measure capacity. We address the measurement in the change detection paradigm, popularized by Luck and Vogel (Nature, 390, 279–281, 1997). Two measures for this task—from Pashler (Perception & Psychophysics, 44, 369–378, 1988) and Cowan (The Behavioral and Brain Sciences, 24, 87–114, 2001), respectively—have been used interchangeably, even though they may yield qualitatively different conclusions. We show that the choice between these two measures is not arbitrary. Although they are motivated by the same underlying discrete-slots working memory model, each is applicable only to a specific task; the two are never interchangeable. In the course of deriving these measures, we discuss subtle but consequential flaws in the underlying discrete-slots model. These flaws motivate revision in the modal model and capacity measures.

Previous studies indicate that visual working memory performance increases with age in childhood but it is not clear why. One main hypothesis has been that younger children are less efficient in their attention, specifically less able to exclude irrelevant items from working memory to make room for relevant items. We examined this hypothesis by measuring visual working memory capacity under a continuum of 5 attention conditions. A recognition advantage was found for items to be attended as opposed to ignored. The size of this attention-related effect was adult-like in young children with small arrays, suggesting that their attention processes are efficient even though their working memory capacity is smaller than that of older children and adults. With a larger working memory load, this efficiency in young children is compromised. The efficiency of attention cannot be the sole explanation for the capacity difference.

Recently, investigators have suggested that visual working memory operates in a manner unaffected by the retention of verbal material. We question that conclusion on the basis of a simple dual-task experiment designed to rule out phonological memory and to identify a more central faculty as the source of a shared limitation. With a visual working memory task in which two arrays of color squares were to be compared, performance was unaffected by concurrent recitation of a two-digit list or a known seven-digit sequence. However, visual working memory performance decreased markedly when paired with a load of seven random digits. This was not a simple tradeoff, inasmuch as errors on the visual array and high digit load tasks tended to co-occur. Working memory for digits and visual information thus are both subject to at least one type of shared limit, not just domain-specific limitations. The nature of the shared limit is discussed.

Openness is one of the central values of science. Open scientific practices such as sharing data, materials and analysis scripts alongside published articles have many benefits, including easier replication and extension studies, increased availability of data for theory-building and meta-analysis, and increased possibility of review and collaboration even after a paper has been published. Although modern information technology makes sharing easier than ever before, uptake of open practices had been slow. We suggest this might be in part due to a social dilemma arising from misaligned incentives and propose a specific, concrete mechanism—reviewers withholding comprehensive review—to achieve the goal of creating the expectation of open practices as a matter of scientific principle.

Examinations of interference between verbal and visual materials in working memory have produced mixed results. If there is a central form of storage (e.g., the focus of attention; Cowan, 2001) then cross-domain interference should be obtained. We examined this question with a visual-array comparison task (Luck & Vogel, 1997) combined with various verbal memory load conditions. Interference between tasks occurred if there was explicit retrieval of the verbal load during maintenance of a visual array. The effect was localized in the maintenance period of the visual task, and was not the result of articulation per se. Interference occurred also when especially large silent verbal and visual loads were held concurrently. These results suggest central storage along with codespecific, passive storage.A simple question that has yielded a complex answer is whether memories in different domains can be actively represented in working memory at the same time. Baddeley and Hitch (1974) and Baddeley (1986) reported only mild interference between various types of cognitive tasks and a verbal memory load. The working-memory theory of Baddeley (1986; see also Baddeley & Logie, 1999) includes separate, passively-held storage faculties for verbal and visuospatial forms of information but some conflict is said to be possible if both forms of information are demanding enough to require the involvement of central executive processes at the same time for rehearsal and/or processing. Given that this central executive involvement is not always necessary, it is perhaps not surprising that examinations of the extent of conflict between two tasks in different domains have yielded mixed results (e.g., Cocchini, Logie, Della Sala, MacPherson, & Baddeley, 2002;Duncan, Martens & Ward, 1997;Jolicoeur, 1999;Luck & Vogel, 1997;Morey & Cowan, 2004;Sanders & Schroots, 1969; Stevanovski & Jolicoeur, 2003).Another theoretical approach to working memory seems to imply somewhat different reasons why visual and verbal tasks would or would not conflict. Whereas, in the model of Baddeley (1986), central-executive processes manipulate information that is held completely within passive types of storage, Cowan (1995Cowan ( , 2001 suggested that some information can be held also in the focus of attention (in addition to passively-held forms of storage). This information in the focus of attention was said to be subject to a capacity limit, as opposed to the temporal limits and interference factors that are prominent for the passively-held stores. A recent amendment of the working-memory model of Baddeley (1986) includes an episodic buffer (Baddeley, 2000), which could similarly be limited in capacity (Baddeley, 2001). With this type of approach, as well, it is still an open question as to when visual and verbal maintenance will conflict.