Change blindness is the striking failure to see large changes that normally would be noticed easily. Over the past decade this phenomenon has greatly contributed to our understanding of attention, perception, and even consciousness. The surprising extent of change blindness explains its broad appeal, but its counterintuitive nature has also engendered confusions about the kinds of inferences that legitimately follow from it. Here we discuss the legitimate and the erroneous inferences that have been drawn, and offer a set of requirements (...) to help separate them. In doing so, we clarify the genuine contributions of change blindness research to our understanding of visual perception and awareness, and provide a glimpse of some ways in which change blindness might shape future research. (shrink)

In a series of three experiments, we explored the nature of implicit representations in change blindness . Using 3 × 3 letter arrays, we asked subjects to locate changes in paired arrays separated by 80 ms ISIs, in which one, two or three letters of a row in the second array changed. In one testing version, a tone followed the second array, signaling a row for partial report . In the other version, no PR was required. After Ss reported whether (...) a change had been detected and the PR had been completed , they were asked to identify a degraded letter trigram that was either novel, or from a previously shown row . Our findings indicate that when CB occurs, both the pre-change and post-change stimulus information primes despite its unavailability to consciousness. Surprisingly, findings also indicate that when change detection occurs only the post-change information primes. (shrink)

Five aspects of visual change detection are reviewed. The first concerns the concept of change itself, in particular the ways it differs from the related notions of motion and difference. The second involves the various methodological approaches that have been developed to study change detection; it is shown that under a variety of conditions observers are often unable to see large changes directly in their field of view. Next, it is argued that this “change blindness” indicates that focused attention is (...) needed to detect change, and that this can help map out the nature of visual attention. The fourth aspect concerns how these results affect our understanding of visual perception—for example, the implication that a sparse, dynamic representation underlies much of our visual experience. Finally, a brief discussion is presented concerning the limits to our current understanding of change detection. (shrink)

When brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced: the changes become extremely difficult to notice, even when they are large, presented repeatedly, and the observer expects them to occur (Rensink, O'Regan, & Clark, 1997). To determine the mechanisms behind this induced "change blindness", four experiments examine its dependence on initial preview and on the nature of the interruptions used. Results support the proposal that representations at (...) the early stages of visual processing are highly volatile, and that focused attention is needed to stabilize them sufficiently to support the perception of change. (shrink)

Previous studies have suggested that visual short-term memory (VSTM) has a storage limit of approximately four items. However, the type of high-threshold (HT) model used to derive this estimate is based on a number of assumptions that have been criticized in other experimental paradigms (e.g., visual search). Here we report findings from nine experiments in which VSTM for color, spatial frequency, and orientation was modeled using a signal detection theory (SDT) approach. In Experiments 1-6, two arrays composed of multiple stimulus (...) elements were presented for 100 ms with a 1500 ms ISI. Observers were asked to report in a yes/no fashion whether there was any difference between the first and second arrays, and to rate their confidence in their response on a 1-4 scale. In Experiments 1-3, only one stimulus element difference could occur (_T_ = 1) while set size was varied. In Experiments 4-6, set size was fixed while the number of stimuli that might change was varied (_T_ = 1, 2, 3, and 4). Three general models were tested against the receiver operating characteristics generated by the six experiments. In addition to the HT model, two SDT models were tried: one assuming summation of signals prior to a decision, the other using a max rule. In Experiments 7-9, observers were asked to directly report the relevant feature attribute of a stimulus presented 1500 ms previously, from an array of varying set size. Overall, the results suggest that observers encode stimuli independently and in parallel, and that performance is limited by internal noise, which is a function of set size. (shrink)