Neural representation of object-specific attentional priority

Humans can flexibly select locations, features, or objects in a visual scene for prioritized processing. Although it is relatively straightforward to manipulate location- and feature-based attention, it is difficult to isolate object-based selection. Because objects are always composed of features, studies of object-based selection can often be interpreted as the selection of a combination of locations and features. Here we examined the neural representation of attentional priority in a paradigm that isolated object-based selection. Participants viewed two superimposed gratings that continuously changed their color, orientation, and spatial frequency, such that the gratings traversed the same exact feature values within a trial. Participants were cued at the beginning of each trial to attend to one or the other grating to detect a brief luminance increment, while their brain activity was measured with fMRI. Using multi-voxel pattern analysis, we were able to decode the attended grating in a set of frontoparietal areas, including anterior intraparietal sulcus (IPS), frontal eye field (FEF), and inferior frontal junction (IFJ). Thus, a perceptually varying object can be represented by patterned neural activity in these frontoparietal areas. We suggest that these areas can encode attentional priority for abstract, high-level objects independent of their locations and features.