A neural‐counting model incorporating refractoriness and spread of excitation: Application to intensity discrimination and loudness estimation for variable‐bandwidth noise stimuli

Abstract

An energy‐based neural‐counting model, incorporating refractoriness and spread of excitation, has recently been applied to intensity discrimination and loudness estimation for pure‐tone stimuli [M. C. Teich and G. Lachs, J. Acoust. Soc. Am. 66, 1738–1749 (1979); G. Lachs and M. C. Teich, J. Acoust. Soc. Am. 69, 774 (1981)]. We now examine the behavior of this model when the stimulus is variable‐bandwidth noise rather than a pure tone. The theoretical predictions are in good agreement with psychophysical data for intensity discrimination [C. E. Bos and E. deBoer, J. Acoust. Soc. Am. 39, 708–715 (1966)] and loudness estimation [B. Scharf, “Loudness,” in Handbook of Perception, Vol. IV, Hearing, edited by E. C. Carterette and M. P. Friedman (Academic, New York, 1981)], pp. 187–242. The functional dependence of the theoretical intensity discrimination and loudness curves on the noise bandwidth is established by the excitation pattern along the basilar membrane. This pattern, in turn, is principally determined by the tuned‐filter characteristics of the neural channels in conjunction with the spectral properties of the stimulus. We appeal neither to stimulus intensity fluctuations nor to critical bands in carrying out our analysis. [Work supported by NSF.]