Sample skewness as a statistical measurement of neuronal tuning sharpness.

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically.

Recurrent connectivity can account for the dynamics of disparity processing in V1.

Disparity tuning measured in the primary visual cortex (V1) is described well by the disparity energy model, but not all aspects of disparity tuning are fully explained by the model. Such deviations from the disparity energy model provide us with insight into how network interactions may play a role in disparity processing and help to solve the stereo correspondence problem. Here, we propose a neuronal circuit model with recurrent connections that provides a simple account of the observed deviations.

Spatial anisotropies and temporal fluctuations in extracellular matrix network texture during early embryogenesis.

Early stages of vertebrate embryogenesis are characterized by a remarkable series of shape changes. The resulting morphological complexity is driven by molecular, cellular, and tissue-scale biophysical alterations. Operating at the cellular level, extracellular matrix (ECM) networks facilitate cell motility.

Relative luminance and binocular disparity preferences are correlated in macaque primary visual cortex, matching natural scene statistics.

Humans excel at inferring information about 3D scenes from their 2D images projected on the retinas, using a wide range of depth cues. One example of such inference is the tendency for observers to perceive lighter image regions as closer. This psychophysical behavior could have an ecological basis because nearer regions tend to be lighter in natural 3D scenes.

Cooperative and competitive interactions facilitate stereo computations in macaque primary visual cortex.

Inferring depth from binocular disparities is a difficult problem for the visual system because local features in the left- and right-eye images must be matched correctly to solve this "stereo correspondence problem." Cortical architecture and computational studies suggest that lateral interactions among neurons could help resolve local uncertainty about disparity encoded in individual neurons by incorporating contextual constraints. We found that correlated activity among pairs of neurons in primary visual cortex depended both on disparity-tuning relationships and the stimuli displayed within the receptive fields of the neurons.