Salamander retinal ganglion cell responses to rich stimuli

Abstract

The retinas phenomenological function is often considered to be well-understood: individual retinal ganglion cells are sensitive to a projection of the light stimulus movie onto a classical center-surround linear filter. Recent models elaborating on this basic framework by adding a second linear filter or spike histories, have been quite successful at predicting ganglion cell spikes for spatially uniform random stimuli, and for random stimuli varying spatially with low resolution. Fitting models for stimuli with more finely grained spatial variations becomes difficult because of the very high dimensionality of such stimuli. We present a method of reducing the dimensionality of a fine one dimensional random stimulus by using wavelets, allowing for several clean predictive linear filters to be found for each cell. For salamander retinal ganglion cells, we find in addition to the spike triggered average, 3 identifiable types of linear filters which modulate the firing of most cells. While some cells can be modeled fairly accurately, many cells are poorly captured, even with as many as 4 filters. The new linear filters we find shed some light on the nonlinearities in the retinas integration of temporal and fine spatial information.