The centroid paradigm: A new method for analyzing feature-based attention

When a viewer attends to “the reds” in a painting while ignoring other hues, he/she gives heightened priority to information from red regions. This general capability of selecting visual information based on its content is called “feature-based attention.” This paper proposes a new conceptualization of feature-based attention in terms of attention filters. An attention filter is a process, initiated by a participant, in the context of a task requiring feature-based attention, that operates broadly across space to modulate the relative effectiveness with which different features in the retinal input influence performance. This paper describes an empirical method for measuring attention filters. This method uses a task in which the participant strives to mouse-click the centroids of a briefly flashed clouds composed of items of different types (e.g., dots of different luminances and sizes), weighting some types of items more strongly than others. In different attention conditions, the target weights for different item-types in the centroid task are varied. The actual weights exerted on the participant’s responses by different item-types in any given attention condition are derived by simple linear regression. Because, on each trial, the centroid paradigm obtains information about the relative effectiveness of all the features in the display, both target and distracter features, and because the subject’s response is a continuous variable in each of two dimensions (versus a simple binary choice as in most previous paradigms), it is remarkably powerful. The number of trials required to estimate an attention filter is an order of magnitude fewer than the number required to investigate much simpler concepts in typical psychophysical attention paradigms .