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Signal Processing in the Retina

Research Summary

Fred Rieke wants to understand how computations of behavioral importance are implemented by biophysical mechanisms. This issue is particularly tractable in sensory systems, largely because the performance of several such systems reaches or approaches fundamental physical limits. This performance leads directly to precise questions about how the underlying processes work; answering these questions is a challenge for our understanding of sensory transduction, synaptic transmission, and neural coding.

Visual sensitivity is striking. In starlight, only about 1 rod in 10,000 absorbs a photon during the ~0.2-sec integration time of rod signals. To complicate matters, all of the rods generate noise that threatens to obscure the signals in the few rods absorbing photons. Cone vision is similarly impressive. Our everyday visual experience relies on detecting subtle changes in contrast, spatial position, and color. But vision does more than detect near-threshold inputs, and the amplification required to detect weak inputs presents a risk of saturating neural responses as lighting conditions change. Such saturation is prevented by a diverse set of adaptational mechanisms. Our broad goal is to understand how biophysical mechanisms operating in the retina contribute to the sensitivity and dynamic range of vision, and by doing so to improve our general understanding of how neural computations are implemented.

The challenges visual performance poses for our understanding of neural function recur throughout the nervous system. Other sensory systems must discriminate weak input signals from noise and accurately represent a wide range of input signals. The auditory system, for example, can detect sounds producing movements of the hair cell stereocilia similar in magnitude to those produced by Brownian motion and yet avoid saturation for sounds millions of times louder. The retina provides an excellent opportunity to study these general issues because the signal and noise properties of each cell type can be measured and the stimuli can be precisely controlled.

Two ganglion cells following a paired recording to study synchronous signaling.

Photon Detection and Rod Vision
The dark-adapted visual system can detect absorption of just a few photons. This performance places strict constraints on how absorbed photons are converted into electrical signals by the rod photoreceptors and how the rod signals are processed. The challenges include generating a reproducible, macroscopic elementary response from a single active receptor molecule, reliable transmission of small synaptic signals, and separation of a signal of interest from cellular noise. We are investigating how these challenges are met.

One source of rod noise of particular interest is trial-to-trial variations in the rod's single-photon responses; these variations are much smaller than expected for signals produced by single molecules—e.g., the charge flowing through an ion channel during its open time. Thus reproducibility presents a general molecular design problem: how is the response produced by a single rhodopsin molecule regulated so that its variability is so much less than expected? We found that variability of the single-photon response depends in a graded and systematic manner on the number of phosphorylation sites on rhodopsin—thus reproducibility is apparently produced by the shutoff of a single rhodopsin molecule through a series of steps, each provided by phosphorylation. This is a substantial departure from conventional models for the shutoff of single molecules. We are testing this idea further by characterizing single-photon responses produced by rods from mice in which the phototransduction cascade has been altered genetically.

Rhodopsin is one of many G protein–coupled receptors (GPCRs) in biology. Detection of single photons by the rods represents an opportunity to understand how the activity of single GPCRs is controlled; the ability to study signals generated by single receptors can, in turn, provide insights not possible from observing the average activity of many receptors. Thus we believe that understanding in biophysical detail how the activity of single rhodopsin molecules is regulated will provide general insight into GPCR function and help identify novel approaches to manipulate GPCR activity.

Cones and Cone Vision
The approach to rod signaling described above builds on years of work relating rod and behavioral sensitivity. We know much less about cones and the retinal readout of the cone signals. What limits does cone noise place on the fidelity of cone vision? How do the multiple parallel readouts of the cone signals work collectively to shape retinal outputs? These are fundamental issues for our understanding of cone vision.

Most of us go through each day blissfully unaware of the limitations of cone vision. Indeed, cone vision is quantitatively impressive. For example, humans can discriminate changes in the wavelength of a monochromatic light of a few nanometers, about 50 times less than the width of the cone spectral sensitivity curves. Noise in the cone responses poses a fundamental limit to this acuity. We do not know, for any property of cone vision, how close behavioral performance comes to the limit set by cone noise. We are working to determine the limits the cone signals place on the sensitivity of cone vision. We will compare these limits with the sensitivity of retinal ganglion cells to test whether the cones or downstream events limit the sensitivity of the retinal output. This comparison, like that for the rod signals described above, is fundamental to how we view retinal processing: if ganglion cell sensitivity reaches limits set by the cones, retinal processing must be efficient and effectively noiseless; if ganglion cells fall short of the cone limit, retinal processing must introduce additional noise.

Cone signals are read out in parallel by multiple retinal circuits. Retinal output cells then integrate signals from multiple parallel circuits to control the pattern of activity sent to higher visual areas. This basic architecture, shared by many other neural circuits, raises the opportunity to study how interactions between parallel circuits control the computation the circuit implements. Furthermore, as lighting conditions change, retinal circuits are repurposed to implement different computations, and such repurposing relies on interactions of upstream parallel circuits. We are working in collaboration with Rachel Wong (University of Washington) to identify which parallel circuits interact, the mechanisms responsible for such interactions, and the consequences for retinal computations. 

The sensitivity of rod-mediated vision has motivated 20 years of work that has made the rods the best understood of the many G protein cascades in biological systems. This work also has had direct medical benefits, as we now understand the mechanisms and have potential treatments for several forms of stationary night blindness. Our long-term goal is to bring a similar clarity to our understanding of cone phototransduction and of the retinal processing of rod and cone signals.

This work is supported in part by a grant from the National Institutes of Health.

As of April 4, 2016

Scientist Profile

University of Washington
Biophysics, Neuroscience