A neural-counting model incorporating refractoriness and spread of excitation. I. Application to intensity discrimination

Abstract

We consider in detail a new mathematical neural‐counting model that is remarkably successful in predicting the correct detection law for pure‐tone intensity discrimination, while leaving Weber’s law intact for other commonly encountered stimuli. It incorporates, in rather simple form, two well‐known effects that become more marked in the peripheral auditory system as stimulus intensity is increased: (1) the spread of excitation along the basilar membrane arising from the tuned‐filter characteristics of individual primary afferent fibers and (2) the saturation of neural counts due to refractoriness. For sufficiently high values of intensity, the slope of the intensity‐discrimination curve is calculated from a simplified (crude saturation) model to be 1−1/4N, where N is the number of poles associated with the tuned‐filter characteristic of the individual neural channels. Since 1?N<∞, the slope of this curve is bounded by 3/4 and 1 and provides a theoretical basis for the ’’near miss’’ to Weber’s law.