Maximizing contrast resolution in the outer retina of mammals

Abstract

The outer retina removes the first-order correlation, the background light level, and thus more efficiently transmits contrast. This removal is accomplished by negative feedback from horizontal cell to photoreceptors. However, the optimal feedback gain to maximize the contrast sensitivity and spatial resolution is not known. The objective of this study was to determine, from the known structure of the outer retina, the synaptic gains that optimize the response to spatial and temporal contrast within natural images. We modeled the outer retina as a continuous 2D extension of the discrete 1D model of Yagi et al. (Proc Int Joint Conf Neural Netw 1: 787–789, 1989). We determined the spatio-temporal impulse response of the model using small-signal analysis, assuming that the stimulus did not perturb the resting state of the feedback system. In order to maximize the efficiency of the feedback system, we derived the relationships between time constants, space constants, and synaptic gains that give the fastest temporal adaptation and the highest spatial resolution of the photoreceptor input to bipolar cells. We found that feedback which directly modulated photoreceptor calcium channel activation, as opposed to changing photoreceptor voltage, provides faster adaptation to light onset and higher spatial resolution. The optimal solution suggests that the feedback gain from horizontal cells to photoreceptors should be ~0.5. The model can be extended to retinas that have two or more horizontal cell networks with different space constants. The theoretical predictions closely match experimental observations of outer retinal function.

Lateral interactions in the outer retina

“…As in cones, horizontal cell to rod feedback may enhance local contrast and contribute to post-receptoral light adaptation by subtracting the average level of surrounding illumination (Burkhardt, 1995; Lipin et al, 2010). Feedback to rods might also contribute to the formation of center-surround receptive fields.…”

Inhibitory mechanisms that generate centre and surround properties in ON and OFF brisk‐sustained ganglion cells in the rabbit retina

“…In the retina, where the basic neural circuitry is well delineated, one role of lateral inhibition is to produce the antagonistic centre‐surround receptive field organization seen in many retinal ganglion cells (Kuffler, 1953). The surround suppresses mean luminance signals and enhances sensitivity to local contrast (Kuffler, 1953; Rodieck & Stone, 1965; Enroth‐Cugell & Robson, 1966; Srinivasan et al 1982; Lipin et al 2010). Suppression of the centre responses of ganglion cells, by stimulation of the receptive field surround, is generated both by horizontal cells at the first synapse between the photoreceptors and bipolar cells in the outer plexiform layer (OPL; Mangel, 1991; Lankheet et al 1992; Dacey et al 2000; Kamermans et al 2001; McMahon et al 2004; Ichinose & Lukasiewicz, 2005), and by inhibitory amacrine cells in the second synaptic layer, the inner plexiform layer (IPL; Thibos & Werblin, 1978; Cook & McReynolds, 1998; Demb et al 1999; Taylor, 1999; Roska et al 2000; Flores‐Herr et al 2001; Zaghloul et al 2007; Passaglia et al 2009).…”

A neurociência computacional no estudo dos processos cognitivos

“…In this sense, computational neuroscience can help understanding the visual system at all three levels of Marr, by presenting models that contribute to the comprehension of visual measurement. For example, many studies use computational models to understand the absorption of photons by photoreceptors at very low light levels (Hamer, Nicholas, Tranchina, Liebman, & Lamb, 2003;Lamb & Pugh, 2006;Lyubarsky & Pugh, 1996), or to analyze the integration of these absorptions by post-receptoral neurons (Berntson, Smith, & Taylor, 2004;Lipin, Smith, & Taylor, 2010).…”