Visual objects contain rich local high-order patterns such as curvature, corners, and junctions. In the standard hierarchical model of visual object recognition, V1 neurons were commonly assumed to code local orientation components of those high-order patterns. Here, by using two-photon imaging in awake macaques and systematically characterizing V1 neuronal responses to an extensive set of stimuli, we found a large percentage of neurons in the V1 superficial layer responded more strongly to complex patterns, such as corners, junctions, and curvature, than to their oriented line or edge components. Our results suggest that those individual V1 neurons could play the role in detecting local high-order visual patterns in the early stage of object recognition hierarchy.
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