Abstract
Retinal ganglion cells convey the visual image from the eye to the brain. They generally encode not the raw image intensity, but local differences in space and changes in time. This is regarded as an evolutionary adaptation to the natural environment, because in the average visual scene, the light intensity at each point tends to be similar to, and thus predictable from, the intensities at neighboring points in space and time. The antagonistic receptive field of a ganglion cell effectively subtracts the predicted intensity from the actual intensity. This reduces the dynamic range of signals that must be encoded by optic nerve fibers with a limited range of firing rates. Yet animals encounter many environments with visual statistics different from the average scene. We found that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields of retinal ganglion cells change after a few seconds in a new visual environment. The changes are adaptive, in that the new receptive field improves predictive coding under the new spatio-temporal image statistics. A network model with plastic synapses can account for the large variety of observed adaptations. We will show results from pharmacological and intracellular recording experiments consistent with this model. [Jpn J Physiol 55 Suppl:S49 (2005)]
