Cascaded Processing of Amplitude Modulation for Natural Sound Recognition

Temporal variation of sound envelope, or amplitude modulation (AM), is essential for auditory perception of natural sounds. Neural representation of stimulus AM is successively transformed while processed by a cascade of brain regions in the auditory system. Here we sought the functional significance of such cascaded transformation of AM representation. We modelled the function of the auditory system with a deep neural network (DNN) optimized for natural sound recognition. Neurophysiological analysis of the DNN revealed that AM representation similar to the auditory system emerged during the optimization. The better-recognizing DNNs exhibited larger similarity to the auditory system. The control experiments suggest that the cascading architecture, the data structure, and the optimization objective may be essential factors for the lower, middle and higher regions, respectively. The results were consistently observed across independent datasets. These results suggest the emergence of AM representation in the auditory system during optimization for natural sound recognition.