In order to record spikes from large populations of retinal ganglion cells, we have established a new recording method in the lab where we use semiconductor chips with more than 4,000 recording sites. We have applied this to simultaneously obtain data from several hundred ganglion cells in retinal tissue obtained from mice or salamanders. We have also developed a novel computational method to identify the layout of excitatory inputs that feed into the recorded ganglion cells.
Based on this information about input signals into ganglion cells, we have furthermore studied how signals are transformed when a ganglion cell pools visual signals under natural stimulation. Particular questions here have been how ganglion cells combine signals over space or over different chromatic channels and how they adapt when visual contrast changes in part of a scene, such as when objects shift around or when the illumination conditions change. We have found that some specific cells combine spatial or chromatic signals linearly, others perform complex computational operations. With respect to adaptation, certain cells tend to represent primarily the object with strongest contrast in their field of view, whereas others remain sensitive to additional objects, thus diversifying the information that is transmitted by different types of ganglion cells to the rest of the brain. When considering stimuli with simulated eye movements, we have observed that it is not the responses of individual ganglion cells that are informative about the motion direction, but that the information rather lies in the relative activity among multiple ganglion cells.
Finally, we have investigated how artificially inserted light-sensitive proteins can be used to recreate natural activity in retinas with degenerated photoreceptors. We have compared activity of ganglion cells under natural and artificial stimulation and found that certain cell-specific response properties, like the temporal extent of evoked activity, are retained under artificial stimulation, whereas others, like the timing of response onsets and the sensitivity to complex stimuli, are altered and require transformations of the stimulus to become more natural.
The work has led to a number of high-profile publications, including in the journals Neuron, Nature Communications, and Trends in Neurosciences. In addition, we have made several electrophysiological datasets and analysis software packages publicly available and presented the results at international conferences as well as at public outreach events.
