Visual shape recognition in primates depends on a multi-stage pathway running from primary visual cortex (V1) to inferotemporal cortex (IT). The mechanisms by which local shape signals from V1 are transformed into selectivity for abstract object categories in IT are unknown. One approach to this issue is to investigate shape representation at intermediate stages in the pathway, such as area V4. We studied 109 V4 cells that appeared sensitive to complex shape in preliminary tests. To achieve a more complete picture of shape representation in V4, we tested each cell with a set of 366 stimuli, constructed by systematically combining convex and concave boundary elements into closed shapes. Using this large, diverse stimulus set, we found that all the cells in our sample responded to a wide variety of shapes and did not appear to encode any single type of global shape. However, for most cells the shapes evoking strongest responses were characterized by a consistent type of boundary conformation at a specific position within the stimulus. For example, a given cell might be tuned for shapes containing concave curvature at the right, with other parts of the shape having little or no effect on responses. Many cells were tuned for more complex boundary configurations (e.g., a convex angle adjacent to a concave curve). We quantified this kind of shape tuning with Gaussian functions on a curvature x position domain. These tuning functions fit the neural responses much better than tuning functions based on edge or axis orientation. Thus individual V4 cells appear to encode moderately complex boundary information at specific locations within larger shapes. This finding suggests that, at intermediate stages in the V1-IT transformation, complex objects are represented at least partly in terms of the configurations and positions of their contour components.

The ventral pathway in visual cortex is responsible for the perception of shape. Area V4 is an important intermediate stage in this pathway, and provides the major input to the final stages in inferotemporal cortex. The role of V4 in processing shape information is not yet clear. We studied V4 responses to contour features (angles and curves), which many theorists have proposed as intermediate shape primitives. We used a large parametric set of contour features to test the responses of 152 V4 cells in two awake macaque monkeys. Most cells responded better to contour features than to edges or bars, and about one-third exhibited systematic tuning for contour features. In particular, many cells were selective for contour feature orientation, responding to angles and curves pointing in a particular direction. There was a strong bias toward convex (as opposed to concave) features, implying a neural basis for the well-known perceptual dominance of convexity. Our results suggest that V4 processes information about contour features as a step toward complex shape recognition.

1. We studied the responses of 103 neurons in visual area V4 of anesthetized macaque monkeys to two novel classes of visual stimuli, polar and hyperbolic sinusoidal gratings. We suspected on both theoretical and experimental grounds that these stimuli would be useful for characterizing cells involved in intermediate stages of form analysis. Responses were compared with those obtained with conventional Cartesian sinusoidal gratings. Five independent, quantitative analyses of neural responses were carried out on the entire population of cells. 2. For each cell, responses to the most effective Cartesian, polar, and hyperbolic grating were compared directly. In 18 of 103 cells, the peak response evoked by one stimulus class was significantly different from the peak response evoked by the remaining two classes. Of the remaining 85 cells, 74 had response peaks for the three stimulus classes that were all within a factor of 2 of one another. 3. An information-theoretic analysis of the trial-by-trial responses to each stimulus showed that all but two cells transmitted significant information about the stimulus set as a whole. Comparison of the information transmitted about each stimulus class showed that 23 of 103 cells transmitted a significantly different amount of information about one class than about the remaining two classes. Of the remaining 80 cells, 55 had information transmission rates for the three stimulus classes that were all within a factor of 2 of one another. 4. To identify cells that had orderly tuning profiles in the various stimulus spaces, responses to each stimulus class were fit with a simple Gaussian model. Tuning curves were successfully fit to the data from at least one stimulus class in 98 of 103 cells, and such fits were obtained for at least two classes in 87 cells. Individual neurons showed a wide range of tuning profiles, with response peaks scattered throughout the various stimulus spaces; there were no major differences in the distributions of the widths or positions of tuning curves obtained for the different stimulus classes. 5. Neurons were classified according to their response profiles across the stimulus set with two objective methods, hierarchical cluster analysis and multidimensional scaling. These two analyses produced qualitatively similar results. The most distinct group of cells was highly selective for hyperbolic gratings. The majority of cells fell into one of two groups that were selective for polar gratings: one selective for radial gratings and one selective for concentric or spiral gratings. There was no group whose primary selectivity was for Cartesian gratings. 6. To determine whether cells belonging to identified classes were anatomically clustered, we compared the distribution of classified cells across electrode penetrations with the distribution that would be expected if the cells were distributed randomly. Cells with similar response profiles were often anatomically clustered. 7. A position test was used to determine whether response profiles were sensitive to pre...