Human-Like Modulation Sensitivity Emerging through Optimization to Natural Sound Recognition.

Natural sounds contain rich patterns of amplitude modulation (AM), which is one of the essential sound dimensions for auditory perception. The sensitivity of human hearing to AM measured by psychophysics takes diverse forms depending on the experimental conditions. Here, we address with a single framework the questions of why such patterns of AM sensitivity have emerged in the human auditory system and how they are realized by our neural mechanisms. Assuming that optimization for natural sound recognition has taken place during human evolution and development, we examined its effect on the formation of AM sensitivity by optimizing a computational model, specifically, a multilayer neural network, for natural sound (namely, everyday sounds and speech sounds) recognition and simulating psychophysical experiments in which the AM sensitivity of the model was assessed. Relatively higher layers in the model optimized to sounds with natural AM statistics exhibited AM sensitivity similar to that of humans, although the model was not designed to reproduce human-like AM sensitivity. Moreover, simulated neurophysiological experiments on the model revealed a correspondence between the model layers and the auditory brain regions. The layers in which human-like psychophysical AM sensitivity emerged exhibited substantial neurophysiological similarity with the auditory midbrain and higher regions. These results suggest that human behavioral AM sensitivity has emerged as a result of optimization for natural sound recognition in the course of our evolution and/or development and that it is based on a stimulus representation encoded in the neural firing rates in the auditory midbrain and higher regions.