Abstract
Neurons in primate V4 exhibit various types of selectivity for contour shapes, including curves, angles, and simple shapes. How are these neurons organized in V4 remains unclear. Using intrinsic signal optical imaging and two-photon calcium imaging, we observed submillimeter functional domains in V4 that contained neurons preferring curved contours over rectilinear ones. These curvature domains had similar sizes and response amplitudes as orientation domains but tended to separate from these regions. Within the curvature domains, neurons that preferred circles or curve orientations clustered further into finer scale subdomains. Nevertheless, individual neurons also had a wide range of contour selectivity, and neighboring neurons exhibited a substantial diversity in shape tuning besides their common shape preferences. In strong contrast to V4, V1 and V2 did not have such contour-shape-related domains. These findings highlight the importance and complexity of curvature processing in visual object recognition and the key functional role of V4 in this process.
Highlights
Shape extraction is crucial for object recognition and is a major function of the primate visual cortex
The results demonstrate that different stimuli types mainly affected the population response amplitudes rather than activating different cells within the curvature domain
We identified 1923 neurons in 10 two-photon imaged locations (Figure 3—figure supplement 1); among them, 788 neurons were in the curvature domains while 1135 neurons were outside of these domains
Summary
Shape extraction is crucial for object recognition and is a major function of the primate visual cortex This process has been reported to occur in the ventral visual pathway (V1-V2-V4-IT) in a hierarchical manner (Connor et al, 2007). Functional maps for faces (Wang et al, 1996; Tsao et al, 2006) and various shape features (Fujita et al, 1992; Tsunoda et al, 2001; Sato et al, 2009) have been reported in IT This processing hierarchy appears to lack functional structures for shape features of intermediate complexity, including curvatures and angles. Given the limited spatial resolution of fMRI signals, these patches were relatively large (at the cm-scale) It remains unclear whether there are submillimeter functional columns for curvatures that are similar to those for edge orientations
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