The contralateral delay activity (CDA) is a negative slow wave sensitive to the number of objects maintained in visual working memory (VWM). In recent years, a growing number of labs started to use the CDA in order to investigate VWM, leading to many fascinating discoveries. Here, we discuss the recent developments and contribution of the CDA in various research fields. Importantly, we report two meta-analyses that unequivocally validate the relationship between the set-size increase in the CDA amplitude and the individual VWM capacity, and between the CDA and filtering efficiency. We further discuss how the CDA was used to study the role of VWM in visual search, multiple object tracking, grouping, binding, and whether VWM capacity allocation is determined by the items’ resolution or instead by the number of objects regardless of their complexity. In addition, we report how the CDA has been used to characterize specific VWM deficits in special populations.
What makes an integrated object in visual working memory (WM)? Past evidence suggested that WM holds all features of multidimensional objects together, but struggles to integrate color-color conjunctions. This difficulty was previously attributed to a challenge in same-dimension integration, but here we argue that it arises from the integration of 2 distinct objects. To test this, we examined the integration of distinct different-dimension features (a colored square and a tilted bar). We monitored the contralateral delay activity, an event-related potential component sensitive to the number of objects in WM. The results indicated that color and orientation belonging to distinct objects in a shared location were not integrated in WM (Experiment 1), even following a common fate Gestalt cue (Experiment 2). These conjunctions were better integrated in a less demanding task (Experiment 3), and in the original WM task, but with a less individuating version of the original stimuli (Experiment 4). Our results identify the critical factor in WM integration at same- versus separate-objects, rather than at same- versus different-dimensions. Compared with the perfect integration of an object's features, the integration of several objects is demanding, and depends on an interaction between the grouping cues and task demands, among other factors.
In the present study, we examined how real-world objects are represented in long-term memory. Two contrasting views exist with regard to this question: one argues that real-world objects are represented as a set of independent features, and the other argues that they form bound integrate representations. In 5 experiments, we tested the different predictions of each view, namely whether the different features of real-world items are remembered and forgotten independently from each other, in a feature-based manner, or conversely are stored and lost in an object-based manner, with all features depending upon each other. Across various stimuli, learning tasks (incidental or explicit), experimental setups (within- or between-subjects design), feature-dimensions, and encoding times, we consistently found that information is forgotten in an object-based manner. When an object ceases to be fully remembered, all of its features are lost, instead of only some of the object’s features being lost whereas other features are still remembered. Furthermore, we found support for a strong form of dependency among the different features, namely a hierarchical structure. We conclude that visual long-term memory is object-based, challenging previous findings.
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