Melissa R. Beck

The role of representational volatility in recognizing pre- and postchange objects.

Theories relating attention to change blindness (CB) imply that representations of objects in the focus of attention are stable and coherent. However, CB occurs for objects in the focus of attention. Here, we explore this apparent contradiction and the possibility that changes can be detected without having a complete and stable representation of the prechange object. The first experiment required observers to recognize a prechange object and a postchange object after viewing arrays of various sizes in which the prechange object was replaced by the postchange object after a brief delay. Results indicated that the representation of the prechange object was strong enough to cue a change but not strong enough to support accurate recognition. The remaining experiments demonstrated that the representation of the prechange object is volatile in that a shift in the display or the presence of a postchange object can disrupt the representation. These findings add to current theories of attention and representations by showing that attention may result in volatile representations that can support change detection without supporting accurate recognition.

A Model of Clutter for Complex, Multivariate Geospatial Displays

Objective: A novel model of measuring clutter in complex geospatial displays was compared with human ratings of subjective clutter as a measure of convergent validity. The new model is called the color-clustering clutter (C3) model. Background: Clutter is a known problem in displays of complex data and has been shown to affect target search performance. Previous clutter models are discussed and compared with the C3 model. Method: Two experiments were performed. In Experiment 1, participants performed subjective clutter ratings on six classes of information visualizations. Empirical results were used to set two free parameters in the model. In Experiment 2, participants performed subjective clutter ratings on aeronautical charts. Both experiments compared and correlated empirical data to model predictions. Results: The first experiment resulted in a .76 correlation between ratings and C3. The second experiment resulted in a .86 correlation, significantly better than results from a model developed by Rosenholtz et al. Outliers to our correlation suggest further improvements to C3. Conclusions: We suggest that (a) the C3 model is a good predictor of subjective impressions of clutter in geospatial displays, (b) geospatial clutter is a function of color density and saliency (primary C3 components), and (c) pattern analysis techniques could further improve C3. Application: The C3 model could be used to improve the design of electronic geospatial displays by suggesting when a display will be too cluttered for its intended audience.

The Roles of Encoding, Retrieval, and Awareness in Change Detection

In the experiment reported here, we examined the processes by which expected (probable) changes are detected more frequently than are unexpected (improbable) changes (the change probability effect; Beck, Angelone, & Levin, 2004). The change probability effect may be caused by a bias toward probable changes during encoding of the prechange aspect, during retrieval of the prechange aspect, or during activation of an explicit response to the change. Participants performed a change detection task for probable and improbable changes while their eye movements were tracked. Change detection performance was superior for probable changes, but long-term memory performance was equivalent for both probable and improbable changes. Therefore, although both probable and improbable prechange aspects were encoded, probable prechange aspects were more likely to be retrieved during change detection. Implicit change detection was also greater for probable changes than for improbable changes, suggesting that the change probability effect is the result of a bias during the retrieval and comparison stage of change detection. The stimuli used in the change detection task may be downloaded from www.psychonomic.org/archive.

Visual search is guided by prospective and retrospective memory

Although there has been some controversy as to whether attention is guided by memory during visual search, recent findings have suggested that memory helps to prevent attention from needlessly reinspecting examined items. Until now, it has been assumed that some form of retrospective memory is responsible for keeping track of examined items and preventing revisitations. Alternatively, some form of prospective memory, such as strategic scanpath planning, could be responsible for guiding attention away from examined items. We used a new technique that allowed us to selectively prevent retrospective or prospective memory from contributing to search. We demonstrated that both retrospective and prospective memory guide attention during visual search.

Explicit memory for rejected distractors during visual search

Although memory for the identities of examined items is not used to guide visual search, identity memory may be acquired during visual search. In all experiments reported here, search was occasionally terminated and a memory test was presented for the identity of a previously examined item. Participants demonstrated memory for the locations of the examined items by avoiding revisits to these items and memory performance for the items’ identities was above chance but lower than expected based on performance in intentional memory tests. Memory performance improved when the foil was not from the search set, suggesting that explicit identity memory is not bound to memory for location. Providing context information during test improved memory for the most recently examined item. Memory for the identities of previously examined items was best when the most recently examined item was tested, contextual information was provided, and location memory was not required.

Knowledge About the Probability of Change Affects Change Detection Performance

The visual system continually selects some information for processing while bypassing the processing of other information, and as a consequence, participants often fail to notice large changes to visual stimuli. In the present studies, the authors investigated whether knowledge about the probability of particular changes occurring over time increased the likelihood that changes that were likely to occur in the real world (probable changes) would be detected. The results of two experiments showed that participants were more likely to detect probable changes. This occurred whether or not they were processing the scene in a meaningful manner or actively searching the scene for changes. Furthermore, participants were unable to accurately predict change detection performance for probable and improbable changes.

Accessing long-term memory representations during visual change detection

In visual change detection tasks, providing a cue to the change location concurrent with the test image (post-cue) can improve performance, suggesting that, without a cue, not all encoded representations are automatically accessed. Our studies examined the possibility that post-cues can encourage the retrieval of representations stored in long-term memory (LTM). Participants detected changes in images composed of familiar objects. Performance was better when the cue directed attention to the post-change object. Supporting the role of LTM in the cue effect, the effect was similar regardless of whether the cue was presented during the inter-stimulus interval, concurrent with the onset of the test image, or after the onset of the test image. Furthermore, the post-cue effect and LTM performance were similarly influenced by encoding time. These findings demonstrate that monitoring the visual world for changes does not automatically engage LTM retrieval.

Implicit learning for probable changes in a visual change detection task.

Previous research demonstrates that implicitly learned probability information can guide visual attention. We examined whether the probability of an object changing can be implicitly learned and then used to improve change detection performance. In a series of six experiments, participants completed 120-130 training change detection trials. In four of the experiments the object that changed color was the same shape (trained shape) on every trial. Participants were not explicitly aware of this change probability manipulation and change detection performance was not improved for the trained shape versus untrained shapes. In two of the experiments, the object that changed color was always in the same general location (trained location). Although participants were not explicitly aware of the change probability, implicit knowledge of it did improve change detection performance in the trained location. These results indicate that improved change detection performance through implicitly learned change probability occurs for location but not shape.

Eyes-On Training and Radiological Expertise An Examination of Expertise Development and Its Effects on Visual Working Memory

Objective: Our aim was to examine the specificity of the effects of acquiring expertise on visual working memory (VWM) and the degree to which higher levels of experience within the domain of expertise are associated with more efficient use of VWM. Background: Previous research is inconsistent on whether expertise effects are specific to the area of expertise or generalize to other tasks that also involve the same cognitive processes. It is also unclear whether more training and/or experience will lead to continued improvement on domain-relevant tasks or whether a plateau could be reached. Method: In Experiment 1, veterinary medicine students completed a one-shot visual change detection task. In Experiment 2, veterinarians completed a flicker change detection task. Both experiments involved stimuli specific to the domain of radiology and general stimuli. Results: In Experiment 1, veterinary medicine students who had completed an “eyes-on” radiological training demonstrated a domain-specific effect in which performance was better on the domain-specific stimuli than on the domain-general stimuli. In Experiment 2, veterinarians again showed a domain-specific effect, but performance was unrelated to the amount of experience veterinarians had accumulated. Conclusion: The effect of experience is domain specific and occurs during the first few years of training, after which a plateau is reached. Application: VWM training in one domain may not lead to improved performance on other VWM tasks. In acquiring expertise, eyes-on training is important initially, but continued experience may not be associated with further improvements in the efficiency of VWM.

Attention shifts or volatile representations: What causes binding deficits in visual working memory?

The current study tested two hypotheses of feature binding memory: The attention hypothesis, which suggests that attention is needed to maintain feature bindings in visual working memory (VWM) and the volatile representation hypothesis, which suggests that feature bindings in memory are volatile and easily overwritten, but do not require sustained attention. Experiment 1 tested the attention hypothesis by measuring shifts of overt attention during the study array of a change detection task; serial shifts of attention did not disrupt feature bindings. Experiments 2 and 3 encouraged encoding of more volatile (Experiment 2) or durable (Experiment 3) representations during the study array. Binding change detection performance was impaired in Experiment 2, but not in Experiment 3, suggesting that binding performance is impaired when encoding supports a less durable memory representation. Together, these results suggest that although feature bindings may be volatile and easily overwritten, attention is not required to maintain feature bindings in VWM.