Probing the role of feature dimension maps in visual cognition - PROJECT SUMMARY When looking for a red ladybug in a bush, our attention may be efficiently guided by the red color among the green leaves. If, instead, finding a green caterpillar is our goal, the same red color would need to be ignored, and instead a moving leaf should guide our search. Searching for an object involves a complex interplay between features of the environment that are unique and capture our attention (e.g., the ladybug) and our current task goals (e.g., look for the movement associated with a green caterpillar). It remains unknown how different brain regions contribute to the guidance of visual attention based on different types of features of the environment, and how activation patterns in these brain regions are impacted by our behavioral goals. Our long-term goal is to understand the principles governing how distributed neural processing systems support flexible visual cognition. Our overall objective, which is the next step in pursuit of our long-term goal, is to ascertain how top- down goals and bottom-up stimulus properties jointly mold activation patterns across feature-selective brain regions. Our central hypothesis is that the core computations supporting attentional selection – bottom-up enhancement of salient locations and top-down enhancement of relevant locations or stimulus dimensions – occur at the level of compartmentalized dimension maps instantiated in feature-selective cortical areas, and these modulations are aggregated into a unified priority map to guide behavior. The rationale for the proposed research is that, once we establish how attentional selection modulates dimension maps in healthy participants, we can build improved diagnostic and therapeutic techniques to understand and treat disorders of attentional control. This hypothesis will be tested across 3 Aims: (1) assay how bottom-up stimulus salience impacts stimulus representations in dimension maps and priority maps; (2) characterize the independent impact of top- down attentional selection on activation profiles within dimension maps, and (3) establish the role of neural dimension maps in guiding attention during visual search tasks. Across all Aims, we will apply model-based neuroimaging analyses to assay stimulus representations in feature-selective retinotopic brain regions measured with fMRI. In Aim 1, participants will perform a fixation task while we present different types of stimuli to measure responses associated with stimulus salience in different features. In Aim 2, participants will selectively attend to one of several feature values defining a stimulus while we manipulate properties of the stimulus display. In Aim 3, participants will perform a demanding visual search task while we manipulate aspects of the task and stimulus display. Overall, this project will generate data to determine the role of dimension maps in guiding visual attention. This project is innovative because it uses model-based neuroimaging analyses to characterize spatial maps carried by feature-selective brain regions during demanding cognitive behavior, and because it tests a key aspect of an important theoretical framework. This project is significant because it will lead to a new understanding of how disparate brain regions collaborate to incorporate stimulus- and task-related factors to guide visual attention.
