Emergence of a contrast-invariant representation of naturalistic texture in macaque visual cortex
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Sensory stimuli vary across a variety of dimensions, like contrast, orientation, or texture. The brain must rely on population representations to distinguish changes in one dimension from changes in another. To understand how the visual system might extract separable stimulus representations, we recorded multiunit neuronal responses to texture images varying along two dimensions: contrast, a property represented as early as the retina, and naturalistic statistical structure, a property that modulates neuronal responses in V2 and V4, but not in V1. We measured how sites in these 3 cortical areas responded to variation in both dimensions. Contrast modulated responses in all areas. In V2 and V4, the presence of naturalistic structure both modulated responses and increased contrast sensitivity. Tuning for naturalistic structure was both strongest and most dispersed in V4. We measured how well populations in each area could support the linear readout of both dimensions. Populations in V2 and V4 could support the linear readout of naturalistic structure, but in V4, this readout was more robust to variations in contrast.
To support flexible behavior, the brain must simultaneously represent different stimulus dimensions. Single neurons are typically modulated by multiple dimensions, and so cannot distinguish them - they must be extracted by decoding neural populations. We studied neuronal responses in three cortical visual areas - V1, V2, V4 - using texture images varying in both contrast and naturalistic image structure. We used population decoders to read out each dimension. In all areas, contrast was well decoded independently of image structure. On the other hand, V1 could not decode image structure independent of contrast, while V2 and V4 could. V4 decoding was greatly superior, because the selectivity of individual sites for texture was more diverse than in V1 or V2.