Retinal Lateral Inhibition Provides the Biological Basis of Long-Range Spatial Induction

Abstract

Retinal lateral inhibition is one of the conventional efficient coding mechanisms in the visual system that is produced by interneurons that pool signals over a neighborhood of presynaptic feedforward cells and send inhibitory signals back to them. Thus, the receptive-field (RF) of a retinal ganglion cell has a center-surround receptive-field (RF) profile that is classically represented as a difference-of-Gaussian (DOG) adequate for efficient spatial contrast coding. The DOG RF profile has been attributed to produce the psychophysical phenomena of brightness induction, in which the perceived brightness of an object is affected by that of its vicinity, either shifting away from it (brightness contrast) or becoming more similar to it (brightness assimilation) depending on the size of the surfaces surrounding the object. While brightness contrast can be modeled using a DOG with a narrow surround, brightness assimilation requires a wide suppressive surround. Early retinal studies determined that the suppressive surround of a retinal ganglion cell is narrow (< 100–300 μm; ‘classic RF’), which led researchers to postulate that brightness assimilation must originate at some post-retinal, possibly cortical, stage where long-range interactions are feasible. However, more recent studies have reported that the retinal interneurons also exhibit a spatially wide component (> 500–1000 μm). In the current study, we examine the effect of this wide interneuron RF component in two biophysical retinal models and show that for both of the retinal models it explains the long-range effect evidenced in simultaneous brightness induction phenomena and that the spatial extent of this long-range effect of the retinal model responses matches that of perceptual data. These results suggest that the retinal lateral inhibition mechanism alone can regulate local as well as long-range spatial induction through the narrow and wide RF components of retinal interneurons, arguing against the existing view that spatial induction is operated by two separate local vs. long-range mechanisms.

A Cortical-Inspired Model for Orientation-Dependent Contrast Perception: A Link with Wilson-Cowan Equations

“…Here, µ : Q → R is the local mean of the initial image f 0 . Such term can encode a global reference to the "Grey-World" principle [3] (in this case µ(x) = 1 2 for any x ∈ Q) or a filtering around x ∈ Q computed either via a single-Gaussian convolution [2] or a sum of Gaussian filters [14], consistently with the modelling of the multiple inhibition effects happening at a retinal-level [24]. Finally, the parameter M ∈ (0, 1] stands for a normalisation constant, while λ > 0 represents a weighting parameter enforcing the attachment of the solution f to the given f 0 .…”

Analysis of retinal and cortical components of Retinex algorithms

“…2.3, an increasing number of physiological studies report the existence of multiple scales of surround profiles (the "classic" 28,30,31,32 and the "extraclassic" [40][41][42] ) in the retinal ganglion cell RF. 36 This is comparable to the combined use of multiscale surrounds in the later version of the NASA Retinex.…”

“…This is based on earlier physiological evidence on the retinal ganglion cell RF, which is often referred to as the "classic" RF. 28,[30][31][32] However, Yeonan-Kim and Bertalmío 36 pointed out that there is accumulating evidence that the spatial profiles of the retinal regulatory interneurons are comprised of multiresolution components [37][38][39] and that the surround part of the ganglion cell exhibits an "extra-classic" suppressive field that subtends much beyond the width of the classic RF. [40][41][42] This means that the retinal spatial processing incorporates a multiresolution surround structure.…”

An adaptive scale Gaussian filter to explain White’s illusion from the viewpoint of lightness assimilation for a large range of variation in spatial frequency of the grating and aspect ratio of the targets

“…Such data are pouring over in the recent years. Data from several laboratories indicate that ( Yeonan-Kim & Bertalmio, 2016 ) there are some varieties of amacrine cells which collect information over a radius of more than 500 micrometers. Recent works on wiry amacrine cell reveal that ( Manookin et al, 2015 ) soma of some of these cells collects information from a distance, which may be larger than 1,000 micrometers or one mm.…”