Department of Physics, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Korea.
Center for Complex Systems, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Korea.
Nat Commun. 2024 Jan 2;15(1):148. doi: 10.1038/s41467-023-44516-0.
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 work as a functional basis for the generalization of natural sound, thereby elucidating its origin. These findings suggest that evolutionary adaptation to process natural sounds can provide an initial blueprint for our sense of music.
音乐几乎存在于每一种社会中，具有普遍的声学特征，并且即使没有音乐训练的经验，人类也会通过独特的神经回路对其进行加工。然而，这些先天特征是如何产生的，以及它们有什么作用，目前还不清楚。在这里，我们使用一种模拟大脑听觉信息处理的人工深度神经网络，证明了通过学习自然声音检测，即使不学习音乐，也可以自发地产生对音乐敏感的单元。这些对音乐敏感的单元可以在多个时间尺度上对音乐的时间结构进行编码，符合大脑中观察到的群体水平的反应特征。我们发现，泛化过程对于音乐敏感性的产生至关重要，并且音乐敏感性可以作为自然声音泛化的功能基础，从而阐明其起源。这些发现表明，对自然声音进行处理的进化适应可以为我们的音乐感知提供初始蓝图。
