Morphological and functional identifications of catfish retinal neurons. III. Functional identification.

TWO MAIN QUESTIONS arise naturally in the study of neural systems: “What does the system do?” and its logical companion and sequel, “How does the system do this?” Answering the first question involves the ability to predict the system response to any stimulus, and it is therefore usually carried out through the performance of suitable stimulus-response experiments. As this endeavor is directed to the discovery of the system function (in its processing of stimuli signals into response signals), we term it functional identification of the system. In this series of papers (parts I, II, and III) we attempt to answer both of these questions for the neural systems in the catfish retina. While part I (24) dealt with answering the structural question and part II (28) dealt with answering the functional question by traditional methods, part III (this paper) concentrates on answering the functional question with the white-noise analysis technique and with pooling the results of parts I, II, and III for the comprehensive identification of the vertebrate retinal neurons. Twenty years ago, approximately, Wiener (49) proposed that a nonlinear system could be identified functionally by stimulating it with a Gaussian white-noise input, i.e., a random signal containing all frequencies within the system bandwidth with equal power (and whose amplitude is distributed in Gaussian fashion). Wiener’s proposal was based on the idea that, since the principle of superposition does not hold for nonlinear system, we would need to test such a system exhaustively with all possible inputs; this is exactly what a white-noise