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Poster C38 in Poster Session C - Friday, August 9, 2024, 11:15 am – 1:15 pm, Johnson Ice Rink
Distractor Representations in Neural Feature Dimension Maps Depend on Searched Feature Dimension
Daniel D. Thayer1, Thomas C. Sprague1; 1University of California, Santa Barbara
The selection of objects in the visual field for attention is based on a combination of image-computable salience and current behavioral relevance. The combination of salience and relevance is reflected by a feature-agnostic priority map that indexes important locations. While attention is ultimately directed based on activation from the aggregate priority map, competition between feature-specific items is reflected within corresponding feature dimension maps (e.g., color or motion map). However, it is unclear how responses within neural feature dimension maps reflect competition between relevant and salient items. Here, we used a visual search task to evaluate how relevant and salient items compete in neural feature dimension maps. We applied a multivariate image reconstruction technique to compute spatial maps from activation patterns in color-selective regions while participants searched for targets among salient distractors, each defined by color or motion. Both targets and distractors were represented in reconstructed spatial maps when items were defined by color. Furthermore, the relevant target feature modulated the distractor strength, consistent with goals prioritizing the entire color dimension map. These results indicate that neural feature dimension maps are crucial for computing attentional priority.
Keywords: Priority Maps Visual Search Attentional Capture fMRI