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The mechanisms involved in transforming early visual signals to curvaturerepresentations in V4 are unknown. We propose a hierarchical model that revealsV1/V2 encodings that are essential components for this transformation to thereported curvature representations in V4. Then, by relaxing the often-imposedprior of a single Gaussian, V4 shape selectivity is learned in the last layerof the hierarchy from Macaque V4 responses. We found that V4 cells integratemultiple shape parts from the full spatial extent of their receptive fieldswith similar excitatory and inhibitory contributions. Our results uncover newdetails in existing data about shape selectivity in V4 neurons that withfurther experiments can enhance our understanding of processing in this area.Accordingly, we propose designs for a stimulus set that allow removing shapeparts without disturbing the curvature signal to isolate part contributions toV4 responses.

Learning a model of shape selectivity in V4 cells reveals shape encoding mechanisms in the brain