Principal components analysis of sources of variability in retinal ganglion cell responses.

An approach to the functional organization of retinal ganglion cell processing in terms of correlation matrices (Levine and Shefner, 1975; 1977a, b; Shefner and Levine, 1979) is extended by applying Principal Components Analysis. This analysis reduces each correlation matrix to a few components which are implicit in the data. The component loadings describe properties of the system in terms of loadings (correlations) of time bins on the underlying components. Each component is identified by the experimental conditions associated with the highest loadings. Mixed conditions are quantitatively interpreted as weighted contributions from the various identified components. This has led to new interpretations of existing data. Several properties of ganglion cell inputs are analyzed in this manner, including ON and OFF processes, center and surround mechanisms, rod and cone inputs, and spatially distinct areas within the receptive field center. Although the details vary, generally one of the components is highly associated with ON processes and the other with OFF and/or MAINTAINED processes. several advantages may be realized through the use of Principal Components Analysis: (1) all of the data contribute to the analysis, (2) the number and relative importance of contributing processes may be assessed, (3) the relative contribution of underlying processes to mixed responses may be assessed, and (4) the most parsimonious representation of the data is obtained.