Though it is clear that it is impossible to store an unlimited amount of information in visual working memory (VWM), the limiting mechanisms remain elusive. While several models of VWM limitations exist, these typically characterize changes in performance as a function of the number of to-be-remembered items. Here, we examine whether changes in spatial attention could better account for VWM performance, independent of load. Across 2 experiments, performance was better predicted by the prioritization of memory items (i.e., attention) than by the number of items to be remembered (i.e., memory load). This relationship followed a power law, and held regardless of whether performance was assessed based on overall precision or any of 3 measures in a mixture model. Moreover, at large set sizes, even minimally attended items could receive a small proportion of resources, without any evidence for a discrete-capacity on the number of items that could be maintained in VWM. Finally, the observed data were best fit by a variable-precision model in which response error was related to the proportion of resources allocated to each item, consistent with a model of VWM in which performance is determined by the continuous allocation of attentional resources during encoding. (PsycINFO Database Record

Visual working memory is a brief, capacity-limited store of visual information that is involved in a large number of cognitive functions. To guide one’s behavior effectively, one must efficiently allocate these limited memory resources across memory items. Previous research has suggested that items are either stored in memory or completely blocked from memory access. However, recent behavioral work proposes that memory resources can be flexibly split across items based on their level of task importance. Here, we investigated the electrophysiological correlates of flexible resource allocation by manipulating the distribution of resources amongst systematically lateralized memory items. We examined the contralateral delay activity (CDA), a waveform typically associated with the number of items held in memory. Across three experiments, we found that, in addition to memory load, the CDA flexibly tracks memory resource allocation. This allocation occurred as early as attentional selection, as indicated by the N2pc. Additionally, CDA amplitude was better-described when fit with a continuous model predicted by load and resources together than when fit with either alone. Our findings show that electrophysiological markers of attentional selection and memory maintenance not only track memory load, but also the proportion of memory resources those items receive.

Working memory (WM) is impaired following sleep loss and may be improved after a nap. The goal of the current study was to better understand sleep-related WM enhancement by: (1) employing a WM task that assesses the ability to hold and report visual representations as well as the fidelity of the reports on a fine scale, (2) investigating neurophysiological properties of sleep and WM capacity as potential predictors or moderators of sleep-related enhancement, and (3) exploring frontal and occipital event-related delay activity to index the neural processing of stimuli in WM. In a within-subjects design, 36 young adults (M = 20, 20 men, 16 women) completed a 300-trial, continuous-report task of visual WM following a 90-min nap opportunity and an equivalent period of wakefulness. Mixed-effect models were used to estimate the odds of successful WM reports and the fidelity of those reports. The odds of a successful report were approximately equal between nap and wake conditions for the start of the task, but by the end, the odds of success were 1.26 times greater in the nap condition. Successful WM reports were more accurate after a nap, independent of the time on task. Neither WM capacity nor any of the sleep variables measured were found to significantly moderate the nap effect on WM. Lastly, napping resulted in amplitude changes for frontal and occipital delay activity relative to the wake condition. The findings are discussed in relation to contemporary models of visual WM and the role of sleep in sustained attention.

1Visual working memory is a brief, capacity-limited store of visual information that is involved in 2 a large number of cognitive functions. To guide one's behavior effectively, one must efficiently 3 allocate these limited memory resources across memory items. Previous research has suggested 4 that items are either stored in memory or completely blocked from memory access. However, 5 recent behavioral work proposes that memory resources can be flexibly split across items based 6 on their level of task importance. Here, we investigated the electrophysiological correlates of 7 flexible resource allocation by manipulating the distribution of resources amongst systematically 8 lateralized memory items. We examined the contralateral delay activity (CDA), a waveform 9 typically associated with the number of items held in memory. Across three experiments, we 10 found that, in addition to memory load, the CDA flexibly tracks memory resource allocation. 11This allocation occurred as early as attentional selection, as indicated by the N2pc. Additionally, 12CDA amplitude was better-described when fit with a continuous model predicted by load and 13 resources together than when fit with either alone. Our findings show that electrophysiological 14 markers of attentional selection and memory maintenance not only track memory load, but also 15 the proportion of memory resources those items receive. 16

Visual working memory (VWM) resources have been shown to be flexibly distributed according to item priority. This flexible allocation of resources may depend on attentional control, an executive function known to decline with age. In this study, we sought to determine how age differences in attentional control affect VWM performance when attention is flexibly allocated amongst targets of varying priority. Participants performed a delayed-recall task wherein item priority was varied. Error was modelled using a three-component mixture model to probe different aspects of performance (precision, guess-rate, and non-target errors). The flexible resource model offered a good fit to the data from both age groups, but older adults showed consistently lower precision and higher guess rates. Importantly, when demands on flexible resource allocation were highest, older adults showed more non-target errors, often swapping in the item that had a higher priority at encoding. Taken together, these results suggest that the ability to flexibly allocate attention in VWM is largely maintained with age, but older adults are less precise overall and sometimes swap in salient, but no longer relevant, items possibly due to their lessened ability to inhibit previously attended information.