Curvature-processing network in macaque visual cortex

Abstract

Our visual environment abounds with curved features. Thus, the goal of understanding visual processing should include the processing of curved features. Using functional magnetic resonance imaging in behaving monkeys, we demonstrated a network of cortical areas selective for the processing of curved features. This network includes three distinct hierarchically organized regions within the ventral visual pathway: a posterior curvature-biased patch (PCP) located in the near-foveal representation of dorsal V4, a middle curvature-biased patch (MCP) located on the ventral lip of the posterior superior temporal sulcus (STS) in area TEO, and an anterior curvature-biased patch (ACP) located just below the STS in anterior area TE. Our results further indicate that the processing of curvature becomes increasingly complex from PCP to ACP. The proximity of the curvature-processing network to the well-known face-processing network suggests a possible functional link between them.curvature patches | face patches | curved Gabor filters D ecades of research have focused on understanding visual feature processing, particularly along the ventral visual pathway. Such studies have shown that neurons in lower-order visual areas (e.g., V1) respond strongly to simple oriented contours (1), whereas neurons in higher-order visual areas (e.g., inferior temporal cortex) respond selectively to more complex image features and/or visual categories (2-4), in ways that are not yet fully understood. To link these extremes in visual information processing, many studies have aimed to clarify the optimal "trigger" features at intermediate levels of the visual cortical hierarchy.Among these features, stimulus curvature has not been well studied. This is surprising because, strictly, all lines are curved to some extent, except for the single exception of a perfectly straight line. This ubiquity of curved shapes also extends to 3D surfaces (5). In nature, where much of our visual system presumably evolved, perfectly flat surfaces are rare. Even the flattest of natural features (e.g., oceans, sandy beaches) are often curved to some extent, due to wind, water motion, and even the curvature of the earth. Thus, it is important to understand curvature processing to fully unravel the steps in cortical visual processing.Among the few studies to test single neuron responses to curvature per se, Gallant et al. (6,7) reported that a significant percentage of neurons in macaque cortical area V4 is selective for curved stimuli. Intriguingly, these authors also noted that neurons preferring curved patterns were often anatomically clustered together. Subsequently, demonstrated that neurons in the parafoveal representation of dorsal V4 respond robustly to the curvature component of complex shapes. To our knowledge, there have been no systematic studies of curvature at levels below V4 in macaques.Intriguingly, some evidence suggests that the processing of curvature may interact selectively with the processing of faces. For instance, perceptual deficits in face reco...

Organization of high-level visual cortex in human infants

“…In subsequent analyses, we sought to constrain the functional interpretation of these responses. Are cortical regions in infants responding to highly specific visual categories124, to broader visual or semantic dimensions56, or to lower-level visual features that co-vary with high-level categories24252627? Do large-scale patterns of response to categories other than faces and scenes change over development?…”

“…Do preferential responses to faces and scenes in infants reflect a high-level category preference, or a bias toward lower-level visual features, such as eccentricity, spatial frequency or rectilinearity (the presence of 90° angles)24252627? We tested whether cortical responses in infants were better predicted by these lower-level visual features than by high-level categories.…”

“…In particular, we focused on high- and low-frequency content and rectilinearity (the presence of 90° angles in an image), which have been argued previously to modulate responses in category-sensitive visual regions242526. Frequency content and rectilinearity measures were computed on individual frames from each movie clip, and averaged across frames for a given clip.…”

Development of the macaque face-patch system

“…On the basis of previous results in adolescents and adults, category-selective domains are correlated with a gradient of curvature/rectilinearity, with face-selective domains being correlated with preference for curvature729. We therefore chose to contrast monkey faces with rectilinear objects.…”

“…9, which show similar spatial organization for scrambled-face responsiveness and face selectivity. Further, it has been previously reported that even in adults face domains are also not absolutely face-selective, being broad enough to include other round objects and even curvy patterns72943. The shared selectivity for faces and scrambled faces cannot be explained by an initial semantically defined face template that is broadened, by experiencing the image statistics of faces, to include other round/curvy things; rather the broad selectivity itself must be innate.…”