Precise visuotopic organization of the blind spot representation in primate V1

Abstract

The optic disk is a region of the retina consisting mainly of ganglion cell axons and blood vessels, which generates a visual scotoma known as the blind spot (BS). Information present in the surroundings of the BS can be used to complete the missing information. However, the neuronal mechanisms underlying these perceptual phenomena are poorly understood. We investigate the topography of the BS representation (BSR) in cortical area V1 of the capuchin monkey, using single and multiple electrodes. Receptive fields (RFs) of neurons inside the BSR were investigated using two distinct automatic bias-free mapping methods. The first method (local mapping) consisted of randomly flashing small white squares. For the second mapping method (global mapping), we used a single long bar that moved in one of eight directions. The latter stimulus was capable of eliciting neuronal activity inside the BSR, possibly attributable to long-range surround activity taking place outside the borders of the BSR. Importantly, we found that the neuronal activity inside the BSR is organized topographically in a manner similar to that found in other portions of V1. On average, the RFs inside the BS were larger than those outside. However, no differences in orientation or direction tuning were found between the two regions. We propose that area V1 exhibits a continuous functional topographic map, which is not interrupted in the BSR, as expected by the distribution of photoreceptors in the retina. Thus V1 topography is better described as “visuotopic” rather than as a discontinuous “retinotopic” map.

Filling-in rivalry: Perceptual alternations in the absence of retinal image conflict

“…Physiological studies have shown that a retinotopic representation of the blind spot exists as early as V1 (Awater, Kerlin, Evans, & Tong, 2005; Azzi, Gattass, Lima, Soares, & Fiorani, 2015; Fiorani, Rosa, Gattass, & Rocha-Miranda, 1992; Komatsu, Kinoshita, & Murakami, 2000, 2002; Matsumoto & Komatsu, 2005). Neurons within the blind spot representation have relatively large receptive fields that extend beyond the borders of the blind spot (Azzi et al, 2015) and can exhibit color (Komatsu et al, 2000; Komatsu et al, 2002) and orientation (Fiorani et al, 1992; Komatsu et al, 2000) selectivity. Thus one might imagine rivalry arising from competition between neurons within the blind spot representation tuned to the orthogonal orientations and conflicting colors of the bars.…”

Did you see it? A Python tool for psychophysical assessment of the human blind spot

“…Detection of border points uses a dot or point visual stimulus to probe the borders of the blind spot. It is the most popular strategy used in blind spot research [9,[25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]. The typical method is for the observer or experimenter to move a small dot stimulus forth and back across the blind spot borders, and for the observer to report when it perceptually "disappears" (into the blind spot), and when it "appears" (from out of the blind spot).…”

A Model for the Diffusive Filling-In Algorithm Operating in Spike Mode

“…Shifts to the left or to the right (or similar shifts along other orientations) have a biological counterpart: in natural systems, specific structures (neural circuits involving long-range connections [20]) known as bipoles [21], [22] implement those shifts. Bipoles are neural circuits composed by a large number of neurons, which can together generate a weighted response that takes into account two input connection types: short-range connections (with smaller weight) and long-range connections (with larger weight).…”