Contours and surface textures provide powerful cues used in image
segmentation and the analysis of object shape. To learn more about how
the visual system extracts and represents these visual cues, we studied
the responses of V2 neurons in awake, fixating monkeys to complex
contour stimuli (angles, intersections, arcs, and circles) and texture
patterns such as non-Cartesian gratings, along with conventional bars
and sinusoidal gratings. Substantial proportions of V2 cells conveyed
information about many contour and texture characteristics associated
with our stimuli, including shape, size, orientation, and spatial
frequency. However, the cells differed considerably in terms of their
degree of selectivity for the various stimulus characteristics. On
average, V2 cells responded better to grating stimuli but were more
selective for contour stimuli. Metric multidimensional scaling and
principal components analysis showed that, as a population, V2 cells
show strong correlations in how they respond to different stimulus
types. The first two and five principal components accounted for 69%
and 85% of the overall response variation, respectively, suggesting
that the response correlations simplified the population representation
of shape information with relatively little loss of information.
Moreover, smaller random subsets of the population carried response
correlation patterns very similar to the population as a whole,
indicating that the response correlations were a widespread property of
V2 cells. Thus, V2 cells extract information about a number of higher
order shape cues related to contours and surface textures and about
similarities among many of these shape cues. This may reflect an
efficient strategy of representing cues for image segmentation and
object shape using finite neuronal resources.
Grasp Exploration for 3D Object Shape Representation Using Probabilistic Map