Category search speeds up face-selective fMRI responses in a non-hierarchical cortical face network

The human brain is extremely efficient at detecting faces in complex visual scenes, but the spatio-temporal dynamics of this remarkable ability, and how it is influenced by category-search, remain largely unknown. In the present study, human subjects were shown gradually-emerging images of faces or cars in visual scenes, while neural activity was recorded using functional magnetic resonance imaging (fMRI). Category search was manipulated by the instruction to indicate the presence of either a face or a car, in different blocks, as soon as an exemplar of the target category was detected in the visual scene. The category selectivity of most face-selective areas was enhanced when participants were instructed to report the presence of faces in gradually decreasing noise stimuli. Conversely, the same regions showed much less selectivity when participants were instructed instead to detect cars. When “face” was the target category, the fusiform face area (FFA) showed consistently earlier differentiation of face versus car stimuli than did the “occipital face area” (OFA). When “car” was the target category, only the FFA showed differentiation of face versus car stimuli. These observations provide further challenges for hierarchical models of cortical face processing and show that during gradual revealing of information, selective category-search may decrease the required amount of information, enhancing and speeding up category-selective responses in the human brain.