The role of sensory adaptation in the retina.

Abstract

Adaptation, a change in response to a sustained stimulus, is a widespread property of sensory systems, occurring at many stages, from the most peripheral energy-gathering structures to neural networks. Adaptation is also implemented at many levels of biological organization, from the molecule to the organ. Despite adaptation's diversity, it is fruitful to extract some unifying principles by considering well-characterized components of the insect visual system. A major function of adaptation is to increase the amount of sensory information an organism uses. The amount of information available to an organism is ultimately defined by its environment and its size. The amount of information collected depends upon the ways in which an organism samples and transduces signals. The amount of information that is used is further limited by internal losses during transmission and processing. Adaptation can increase information capture and reduce internal losses by minimizing the effects of physical and biophysical constraints. Optical adaptation mechanisms in compound eyes illustrate a common trade-off between energy (quantum catch) and acuity (sensitivity to changes in the distribution of energy). This trade-off can be carefully regulated to maximize the information gathered (i.e. the number of pictures an eye can reconstruct). Similar trade-offs can be performed neurally by area summation mechanisms. Light adaptation in photoreceptors introduces the roles played by cellular constraints in limiting the available information. Adaptation mechanisms prevent saturation and, by trading gain for temporal acuity, increase the rate of information uptake. By minimizing the constraint of nonlinear summation (imposed by membrane conductance mechanisms) a cell's sensitivity follows the Weber-Fechner law. Thus, a computationally advantageous transformation is generated in response to a cellular constraint. The synaptic transfer of signals from photoreceptors to second-order neurones emphasizes that the cellular constraints of nonlinearity, noise and dynamic range limit the transmission of information from cell to cell. Synaptic amplification is increased to reduce the effects of noise but this resurrects the constraint of dynamic range. Adaptation mechanisms, both confined to single synapses and distributed in networks, remove spatially and temporally redundant signal components to help accommodate more information within a single cell. The net effect is a computationally advantageous removal of the background signal. Again, the cellular constraints on information transfer have dictated a computationally advantageous operation.