Investigating shape and function relationship in retinal ganglion cells.

Abstract

This article addresses the investigation of the relationship between neural shape and function in cat retinal ganglion cells in terms of representative morphological features. More specifically, a series of geometrical measures is extracted from two-dimensional images of these cells, and pattern recognition methods are applied in order to quantify the differentiation between the two classes (i.e., alpha, beta). The morphological measures cover several of the more meaningful geometrical features of neuronal cells, including: (a) the distribution of angles along the cell contours considering several smoothing degrees; (b) the overall interaction between the cell arborization and the surrounding space, quantified in terms of the multiscale fractal dimension; and (c) the distribution of width and extent of the dendritic processes. Several combinations of such morphological measures are assessed with respect to the separability of the classes. The obtained results indicate that the methods based on statistic relation between segment length and segment diameter, and the method of multiscale angle entropy not only successfully encapsulated a large amount of experimental data into relatively compact patterns but also marked off various ganglion cells into befit groups. On the other hand, the method of neuron classification based on fractal dimension resulted relatively less effective for class separation.