Abstract
Almost nothing is known about the spatial structure of V1 receptive fields at the center-of-gaze, yet these neurons are the building blocks for high acuity vision. This knowledge gap is due to the technical challenges in measuring receptive fields (RFs) at the resolution of single-cone inputs present in the retina (~1 arcminute resolution). Given the distinct anatomical and physiological characteristics of foveal retina, it is possible that RFs in foveal V1 are not simply finer versions of parafoveal cells and may have distinctive aspects of visual processing. Here, we developed a model-based approach leveraging neurophysiological data to refine eye position estimates beyond the limits of hardware-based eye trackers using chronic array recordings of foveal RFs in awake fixating macaque. We presented spatiochromatic noise stimuli while recording across cortical layers, using acute laminar arrays sampling many different columns. We applied data-driven nonlinear models to investigate how subcortical inputs are integrated in V1. We recovered detailed spatial RF structure from 429 cells spanning the very center of gaze up to 2o eccentricity. Foveal V1 cells showed a diversity of RF types; some cells were unmodulated by cone-opponent signals (“luminance-only”), and others were modulated by both luminance and cone-opponent signals. RFs were as small as 4 arcminutes, with features subtending ~2 arcminutes. Luminance-only cells had the finest spatial structure RFs (median RF width = 6 arcmin) and typically showed nonlinear responses; cells modulated by cone-opponent signals integrated over larger areas (median RF width = 12 arcmin) and were more likely to be linear. Even within individual cells, the luminance component had finer spatial RF structure than the cone-opponent components, suggesting limits on spatial acuity for cone-opponent computations. Our measurements offer the first detailed observations of spatiochromatic processing in foveal V1 and offer clues to how V1 RFs are constructed from the photoreceptor mosaic.