Spontaneous emergence of rudimentary music detectors in deep neural networks.

ABSTRACT: Music exists in almost every society, has universal acoustic features, and is processed by distinct neural circuits in humans even with no experience of musical training. However, it remains unclear how these innate characteristics emerge and what functions they serve. Here, using an artificial deep neural network that models the auditory information processing of the brain, we show that units tuned to music can spontaneously emerge by learning natural sound detection, even without learning music. The music-selective units encoded the temporal structure of music in multiple timescales, following the population-level response characteristics observed in the brain. We found that the process of generalization is critical for the emergence of music-selectivity and that music-selectivity can wo

SUBMITTER: Kim G 

PROVIDER: S-EPMC10761941 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature