Abstract:

PURPOSE: When multiple stimuli are present in the visual ?eld, competitive interactions between stimuli could be biased by stimulus-driven and attention-driven processes. To study the neural mechanisms underlying multiple-stimulus encoding, we used fMRI with decoding and encoding model to estimate the orientation-selective responses in human visual cortex to parafoveally presented Gabor arrays.
METHODS: In an array, a center Gabor (eccentricity = 2.5°) was surrounded by eight ?anking Gabors (0.75° from the center Gabor). By manipulating the configuration of the flankers, we introduced crowding effect in the multi-stimulus displays at di?erent levels (non-crowded, less-crowded, and more-crowded condition). In the scan, observers performed tasks unrelated to orientation. Using forward encoding model, we decomposed the multivoxel response in each visual area into responses of a hypothetical set of orientation-selective channels.
RESULTS: For non-crowded condition, when selective attention was on the entire array, the orientation response to the array was dominated by the orientation of the flankers. However, when selective attention was directed to the center Gabor, the orientation response began to reflect the orientation of the center Gabor in extrastriate areas: the orientation selectivity for the center Gabor was strongest in V4 while weakest in V1. For less-crowded condition, with directed attention, orientation information was encoded in V1 as an ensemble, which could not be retrieved in downstream visual areas. For more-crowded condition, attention had little e?ect in recovering the orientation information in all the visual areas. 
CONCLUSIONS: These ?ndings suggest that attention resolves the competition among multiple stimuli by counteracting the in?uences of nearby stimuli, resulting in enhanced information processing at the attended location. This process of biased competition appears to be cumulative along the visual-processing hierarchy and became most significant in V4. However, crowding signi?cantly diminished this role of attention on image processing.

Key words: Crowding, Attention, fMRI, Encoding model