Searching for semantics in the retinal code

This paper deals with retinal code semantics by introducing a new approach for the functional classification of retinal ganglion cells based on their firing patterns and coding capabilities. Multielectrode extracellular recordings were obtained from ganglion cell populations in isolated superfused albino rabbit retina using a rectangular array of 100 microelectrodes (Utah's array). To identify classes or groups of neurons that behave similarly two spike train analysis methods including autocorrelations and post-stimulus time histograms (PSTHs) have been used. Information theory (IT) permits to assess the quality and reliability of the subpopulations obtained. Furthermore correlations between the cells of each class have been studied. The most effective clustering strategy was achieved by using the autocorrelations of the recorded cells. The method was useful for defining subsets of retinal ganglion cells, which share similar temporal responses, identifying the best subset coder for different visual parameters.