Although the primary visual cortex (V1) is one of the most extensively studied areas of the primate brain, very little is known about how the far periphery of visual space is represented in this area. We characterized the physiological response properties of V1 neurons in anaesthetized marmoset monkeys, using high-contrast drifting gratings. Comparisons were made between cells with receptive fields located in three regions of V1, defined by eccentricity: central (3–5°), near peripheral (5–15°), and far peripheral (>50°). We found that orientation selectivity of individual cells was similar from the center to the far periphery. Nonetheless, the proportion of orientation-selective neurons was higher in central visual field representation than in the peripheral representations. In addition, there were similar proportions of cells representing all orientations, with the exception of the representation of the far periphery, where we detected a bias favoring near-horizontal orientations. The proportions of direction-selective cells were similar throughout V1. When the center/surround organization of the receptive fields was tested with gratings with varying diameters, we found that the population of neurons that was suppressed by large gratings was smaller in the far periphery, although the strength of suppression in these cells tended to be stronger. In addition, the ratio between the diameters of the excitatory centers and suppressive surrounds was similar across the entire visual field. These results suggest that, superimposed on the broad uniformity of V1, there are subtle physiological differences, which indicate that spatial information is processed differently in the central versus far peripheral visual fields.

The neural mechanisms driving perception and saccades during search use information about the target but are also based on an inhibitory surround not present in the target luminance profile (e.g., Eckstein et al., 2007). Here, we ask whether these inhibitory surrounds might reflect a strategy that the brain has adapted to optimize the search for targets in natural scenes. To test this hypothesis, we sought to estimate the best linear template (behavioral receptive field), built from linear combinations of Gabor channels representing V1 simple cells in search for an additive Gaussian target embedded in natural images. Statistically nonstationary and non-Gaussian properties of natural scenes preclude calculation of the best linear template from analytic expressions and require an iterative optimization method such as a virtual evolution via a genetic algorithm. Evolved linear receptive fields built from linear combinations of Gabor functions include substantial inhibitory surround, larger than those found in humans performing target search in white noise. The inhibitory surrounds were robust to changes in the contrast of the signal, generalized to a larger calibrated natural image data set, and tasks in which the signal occluded other objects in the image. We show that channel nonlinearities can have strong effects on the observed linear behavioral receptive field but preserve the inhibitory surrounds. Together, the results suggest that the apparent suboptimality of inhibitory surrounds in human behavioral receptive fields when searching for a target in white noise might reflect a strategy to optimize detection of signals in natural scenes. Finally, we contend that optimized linear detection of spatially compact signals in natural images might be a new possible hypothesis, distinct from decorrelation of visual input and sparse representations (e.g., Graham et al., 2006), to explain the evolution of center–surround organization of receptive fields in early vision.