Sparse coding has long been recognized as a primary goal of image transformation in the visual system [1–4]. Sparse coding in early visual cortex is achieved by abstracting local oriented spatial frequencies  and by excitatory/inhibitory surround modulation . Object responses are thought to be sparse at subsequent processing stages [7, 8], but neural mechanisms for higher-level sparsification are not known. Here, convergent results from macaque area V4 neural recording and simulated V4 populations trained on natural object contours suggest that sparse coding is achieved in midlevel visual cortex by emphasizing representation of acute convex and concave curvature. We studied 165 V4 neurons with a random, adaptive stimulus strategy to minimize bias and explore an unlimited range of contour shapes. V4 responses were strongly weighted toward contours containin
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