Precue effects in visual search: data or resource limited?

Precuing an observer as to where a target is more likely to occur in a subsequent visual array can increase the detectability (d') of a target at that location. This is often attributed to the observer's increased allocation of some limited cognitive resource ("attention") to the cued location. Two experiments are reported which are difficult to interpret in this way even though they involve similar cue effects. The first involves postcuing a location well after the array but before the observer responds, so that the cue can influence the response but not the observation. The second involves precuing, but with slow sequential presentation of array elements prior to the response, so the observer need not share any limited resource while processing each element in turn. Enhanced detectability similar to that produced with precues and simultaneous presentation of elements is shown to occur in each experiment. An alternative data-limited (rather than resource-limited) interpretation of these effects is provided by a mathematical model in which the observer integrates equally noisy or degraded internal representations of the array elements, but gives more weight to cued elements in selecting a response. Theoretical parameters of the model are shown to provide separate measures of both an observer's overall sensitivity and precue effects in cost-benefit analyses of cuing data.

Comments on Batchelder and Riefer's multinomial model for source monitoring.

Kinchla criticizes Batchelder and Riefer's multinomial model for source monitoring, primarily its high-threshold assumptions, and he advocates an approach based on statistical decision theory (SDT). In this reply, the authors lay out some of the considerations that led to their model and then raise some specific concerns with Kinchla's critique. The authors point out that most of his criticisms are drawn from contrasting the high threshold and the Gaussian, equal-variance SDT models on receiver operating characteristics (ROC) curves for yes-no recognition memory. They indicate how source monitoring is more complicated than yes-no recognition and question the validity of standard ROC analyses in source monitoring. The authors argue that their model is a good approximation for measuring differences between sources on old-new detection and that it has the ability to measure source discrimination as well as detection. The authors also explore a low-threshold multinomial model and discuss the application of SDT models to source monitoring.