A spherical model for orientation and spatial–frequency tuning in a cortical hypercolumn

Abstract

A theory is presented of the way in which the hypercolumns in primary visual cortex (V1) are organized to detect important features of visual images, namely local orientation and spatial–frequency. Given the existence in V1 of dual maps for these features, both organized around orientation pinwheels, we constructed a model of a hypercolumn in which orientation and spatial–frequency preferences are represented by the two angular coordinates of a sphere. The two poles of this sphere are taken to correspond, respectively, to high and low spatial–frequency preferences. In Part I of the paper, we use mean–field methods to derive exact solutions for localized activity states on the sphere. We show how cortical amplification through recurrent interactions generates a sharply tuned, contrast–invariant population response to both local orientation and local spatial frequency, even in the case of a weakly biased input from the lateral geniculate nucleus (LGN). A major prediction of our model is that this response is non–separable with respect to the local orientation and spatial frequency of a stimulus. That is, orientation tuning is weaker around the pinwheels, and there is a shift in spatial–frequency tuning towards that of the closest pinwheel at non–optimal orientations. In Part II of the paper, we demonstrate that a simple feed–forward model of spatial–frequency preference, unlike that for orientation preference, does not generate a faithful representation when amplified by recurrent interactions in V1. We then introduce the idea that cortico–geniculate feedback modulates LGN activity to generate a faithful representation, thus providing a new functional interpretation of the role of this feedback pathway. Using linear filter theory, we show that if the feedback from a cortical cell is taken to be approximately equal to the reciprocal of the corresponding feed–forward receptive field (in the two–dimensional Fourier domain), then the mismatch between the feed–forward and cortical frequency representations is eliminated. We therefore predict that cortico–geniculate feedback connections innervate the LGN in a pattern determined by the orientation and spatial–frequency biases of feed–forward receptive fields. Finally, we show how recurrent cortical interactions can generate cross–orientation suppression.