A normalized contrast-encoding model exhibits bright/dark asymmetries similar to early visual neurons

Image luminance changes contrast sensitivity in visual cortex

Accurate measures of contrast sensitivity are important for evaluating visual disease progression and for navigation safety. Previous measures suggested that cortical contrast sensitivity was constant across widely different luminance ranges experienced indoors and outdoors. Against this notion, here, we show that luminance range changes contrast sensitivity in both cat and human cortex, and the changes are different for dark and light stimuli. As luminance range increases, contrast sensitivity increases more within cortical pathways signaling lights than those signaling darks. Conversely, when the luminance range is constant, light-dark differences in contrast sensitivity remain relatively constant even if background luminance changes. We show that a Naka-Rushton function modified to include luminance range and light-dark polarity accurately replicates both the statistics of light-dark features in natural scenes and the cortical responses to multiple combinations of contrast and luminance. We conclude that differences in light-dark contrast increase with luminance range and are largest in bright environments.

A Novel Display System Reveals Anisotropic Polarization Perception in the Motion Vision of the Butterfly Papilio xuthus

While the linear polarization of light is virtually invisible to humans, many invertebrates' eyes can detect it. How this information is processed in the nervous system, and what behavioral function it serves, are in many cases unclear. One reason for this is the technical difficulty involved in presenting images or video containing polarization contrast, particularly if intensity and/or color contrast is also required. In this primarily methods-focused article, we present a novel technique based on projecting video through a synchronously rotating linear polarizer. This approach allows the intensity, angle of polarization, degree of linear polarization, and potentially also color of individual pixels to be controlled independently. We characterize the performance of our system, and then use it to investigate the relationship between polarization and motion vision in the swallowtail butterfly Papilio xuthus. Although this animal has photoreceptors sensitive to four different polarization angles, we find that its motion vision cannot distinguish between diagonally-polarized and unpolarized light. Furthermore, it responds more strongly to vertically-polarized moving objects than horizontally-polarized ones. This implies that Papilio's polarization-based motion detection employs either an unbalanced two-channel (dipolatic) opponent architecture, or possibly a single-channel (monopolatic) scheme without opponent mechanisms.

A normalized contrast-encoding model exhibits bright/dark asymmetries similar to early visual neurons

Biological sensory systems share a number of organizing principles. One such principle is the formation of parallel streams. In the visual system, information about bright and dark features is largely conveyed via two separate streams: the ON and OFF pathways. While brightness and darkness can be considered symmetric and opposite forms of visual contrast, the response properties of cells in the ON and OFF pathways are decidedly asymmetric. Here, we ask whether a simple contrast‐encoding model predicts asymmetries for brights and darks that are similar to the asymmetries found in the ON and OFF pathways. Importantly, this model does not include any explicit differences in how the visual system represents brights and darks, but it does include a common normalization mechanism. The phenomena captured by the model include (1) nonlinear contrast response functions, (2) greater nonlinearities in the responses to darks, and (3) larger responses to dark contrasts. We report a direct, quantitative comparison between these model predictions and previously published electrophysiological measurements from the retina and thalamus (guinea pig and cat, respectively). This work suggests that the simple computation of visual contrast may account for a range of early visual processing nonlinearities. Assessing explicit models of sensory representations is essential for understanding which features of neuronal activity these models can and cannot predict, and for investigating how early computations may reverberate through the sensory pathways.