Article

Interference Within the Focus of Attention: Working Memory Tasks Reflect More Than Temporary Maintenance

Journal of Experimental Psychology Learning Memory and Cognition (Impact Factor: 3.1). 05/2012; 39(1). DOI: 10.1037/a0028467
Source: PubMed

ABSTRACT One approach to understanding working memory (WM) holds that individual differences in WM capacity arise from the amount of information a person can store in WM over short periods of time. This view is especially prevalent in WM research conducted with the visual arrays task. Within this tradition, many researchers have concluded that the average person can maintain approximately 4 items in WM. The present study challenges this interpretation by demonstrating that performance on the visual arrays task is subject to time-related factors that are associated with retrieval from long-term memory. Experiment 1 demonstrates that memory for an array does not decay as a product of absolute time, which is consistent with both maintenance- and retrieval-based explanations of visual arrays performance. Experiment 2 introduced a manipulation of temporal discriminability by varying the relative spacing of trials in time. We found that memory for a target array was significantly influenced by its temporal compression with, or isolation from, a preceding trial. Subsequent experiments extend these effects to sub-capacity set sizes and demonstrate that changes in the size of k are meaningful to prediction of performance on other measures of WM capacity as well as general fluid intelligence. We conclude that performance on the visual arrays task does not reflect a multi-item storage system but instead measures a person's ability to accurately retrieve information in the face of proactive interference. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Download full-text

Full-text

Available from: Randall Engle, Jun 29, 2015
1 Follower
 · 
121 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Bleckley, Durso, Crutchfield, Engle, and Khanna (Psychonomic Bulletin & Review, 10, 884-889, 2003) found that visual attention allocation differed between groups high or low in working memory capacity (WMC). High-span, but not low-span, subjects showed an invalid-cue cost during a letter localization task in which the letter appeared closer to fixation than the cue, but not when the letter appeared farther from fixation than the cue. This suggests that low-spans allocated attention as a spotlight, whereas high-spans allocated their attention to objects. In this study, we tested whether utilizing object-based visual attention is a resource-limited process that is difficult for low-span individuals. In the first experiment, we tested the uses of object versus location-based attention with high and low-span subjects, with half of the subjects completing a demanding secondary load task. Under load, high-spans were no longer able to use object-based visual attention. A second experiment supported the hypothesis that these differences in allocation were due to high-spans using object-based allocation, whereas low-spans used location-based allocation.
    Memory & Cognition 11/2014; 43(3). DOI:10.3758/s13421-014-0485-z · 1.92 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: During the retention interval of a working memory task, presenting a retro-cue directs attention to 1 of the items in working memory. Testing the cued item leads to faster and more accurate responses. We contrasted 5 explanations of this benefit: (a) removal of noncued items, (b) strengthening of the cued item, (c) protection from probe interference, (d) protection from degradation, and (e) prioritization during the decision process. Experiment 1 showed that retro-cues reduced the set size effect in a visual recognition task, and did so increasingly with more time available to use the retro-cue. This finding is predicted only by Hypotheses 1 and 2. Hypotheses 3 through 5 were ruled out as explanations of the retro-cue benefit in this experiment. In Experiments 2 and 3, participants encoded 2 sequentially presented memory sets. In half of the trials, 1 item from the first set was retro-cued during the interset interval. Retro-cues improved memory for the second set. This reloading benefit is predicted only by the removal hypothesis: Irrelevant contents are removed from working memory, freeing capacity to encode new contents. Experiment 3 also yielded evidence that strengthening of the cued item might contribute to the retro-cue effect. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
    Journal of Experimental Psychology Human Perception & Performance 04/2014; 40(3). DOI:10.1037/a0036331 · 3.11 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Working memory capacity is traditionally treated as a unitary construct that can be explained using one cognitive mechanism (e.g., storage, attention control). Several recent studies have, however, demonstrated that multiple mechanisms are needed to explain individual differences in working memory capacity. The present study focuses on three such mechanisms: Maintenance/disengagement in primary memory, retrieval from secondary memory, and attention control. Structural equation modeling reveals that each of these mechanisms is important to explaining individual differences in working memory capacity. Further analyses reveal that the degree to which these mechanisms are apparent may be driven by the type of task used to operationalize working memory capacity. Specifically, complex span (processing and storage) and visual arrays (change detection) performance is strongly related to a person’s attention control, while running memory span (memory for last n items on a list) performance has a relationship to primary memory that is apparent above-and-beyond other working memory tasks. Finally, regardless of the working memory task that is used, it is found that primary and secondary memory fully explain the relationship of working memory capacity to general fluid intelligence.
    Journal of Memory and Language 04/2014; 72:116–141. DOI:10.1016/j.jml.2014.01.004 · 2.65 Impact Factor