Computational models posit that visual attention is guided by activity within spatial maps that index the image-computable salience and the behavioral relevance of objects in the scene. These spatial maps are theorized to be instantiated as activation patterns across a series of retinotopic visual regions in occipital, parietal, and frontal cortex. Whereas previous research has identified sensitivity to either the behavioral relevance or the image-computable salience of different scene elements, the simultaneous influence of these factors on neural "attentional priority maps" in human cortex is not well understood. We tested the hypothesis that visual salience and behavioral relevance independently impact the activation profile across retinotopically organized cortical regions by quantifying attentional priority maps measured in human brains using functional MRI while participants attended one of two differentially salient stimuli. We found that the topography of activation in priority maps, as reflected in the modulation of region-level patterns of population activity, independently indexed the physical salience and behavioral relevance of each scene element. Moreover, salience strongly impacted activation patterns in early visual areas, whereas later visual areas were dominated by relevance. This suggests that prioritizing spatial locations relies on distributed neural codes containing graded representations of salience and relevance across the visual hierarchy. NEW & NOTEWORTHY We tested a theory which supposes that neural systems represent scene elements according to both their salience and their relevance in a series of "priority maps" by measuring functional MRI activation patterns across human brains and reconstructing spatial maps of the visual scene. We found that different regions indexed either the salience or the relevance of scene items, but not their interaction, suggesting an evolving representation of salience and relevance across different visual areas.
Keywords: computational neuroimaging; fMRI; inverted encoding model; priority map; visual spatial attention.