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...

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.

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.

A wealth of neuroscience evidence demonstrates that aerobic fitness enhances structural brain plasticity, promoting the development of gray matter volume and maintenance of white matter integrity within networks for executive function, attention, learning, and memory. However, the role of aerobic fitness in shaping the functional brain connectome remains to be established. The present work therefore investigated the effects of aerobic fitness (as measured by VO2max) on individual differences in whole-brain functional connectivity assessed from resting state fMRI data. Using a connectome-wide association study, we identified significant brain-fitness relationships within a large sample of healthy young adults (N = 242). The results revealed several regions within frontal, temporal, parietal, and cerebellar cortex, having significant association with aerobic fitness. We further characterized the influence of these regions on 7 intrinsic connectivity networks, demonstrating the greatest association with networks that are known to mediate the beneficial effects of aerobic fitness on executive function (frontoparietal network), attention and learning (dorsal and ventral attention network), and memory (default mode network). In addition, we provide evidence that connectivity strength between these regions and the frontoparietal network is predictive of individuals' fluid intelligence.

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