Abstract
Computational theories posit that attention is guided by a combination of spatial maps for individual features that can be dynamically weighted according to task goals. Consistent with this framework, when a stimulus contains several features, attending to one or another feature results in stronger fMRI responses in regions preferring the attended feature. We hypothesized that multivariate activation patterns across feature-responsive cortical regions form spatial 'feature dimension maps', which combine to guide attentional priority. We tested this prediction by reconstructing spatial maps from fMRI activation patterns across retinotopic regions of visual cortex while participants performed a feature-selective attention task. Participants viewed a peripheral visual stimulus at a random location which always contained moving colored dots. On each trial, participants were precued to report the predominant direction of motion or color of the stimulus, or to attend fixation. Stimulus representations in reconstructed maps based on a spatial inverted encoding model were selectively enhanced in color-selective regions when color was attended, and in motion-selective regions when motion was attended. While enhancement was localized to the stimulus position in color-selective regions, modulations in motion-selective regions was consistent with a more global enhancement when motion was task relevant. These results suggest feature-selective cortical regions support 'neural feature dimension maps': spatial maps of different visual features that are dynamically reweighted based on task demands to guide visual behavior to the most relevant locations based on important features.