Department of Mechanical Engineering, University of Houston, Houston, TX 77204.
Department of Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07102.
Proc Natl Acad Sci U S A. 2023 Jan 31;120(5):e2216146120. doi: 10.1073/pnas.2216146120. Epub 2023 Jan 24.
Some people, entirely untrained in music, can listen to a song and replicate it on a piano with unnerving accuracy. What enables some to "hear" music so much better than others? Long-standing research confirms that part of the answer is undoubtedly neurological and can be improved with training. However, are there structural, physical, or engineering attributes of the human hearing mechanism apparatus (i.e., the hair cells of the internal ear) that render one human innately superior to another in terms of propensity to listen to music? In this work, we investigate a physics-based model of the electromechanics of the hair cells in the inner ear to understand why a person might be physiologically better poised to distinguish musical sounds. A key feature of the model is that we avoid a "black-box" systems-type approach. All parameters are well-defined physical quantities, including membrane thickness, bending modulus, electromechanical properties, and geometrical features, among others. Using the two-tone interference problem as a proxy for musical perception, our model allows us to establish the basis for exploring the effect of external factors such as medicine or environment. As an example of the insights we obtain, we conclude that the reduction in bending modulus of the cell membranes (which for instance may be caused by the usage of a certain class of analgesic drugs) or an increase in the flexoelectricity of the hair cell membrane can interfere with the perception of two-tone excitation.
有些人完全没有接受过音乐训练，却能听一首歌并在钢琴上以惊人的准确度再现它。是什么让一些人比其他人更能“听”音乐？长期以来的研究证实，部分答案无疑是神经学方面的，可以通过训练来提高。然而，人类听觉机制（即内耳的毛细胞）的结构、物理或工程属性是否会使人在听音乐的倾向方面天生优于他人？在这项工作中，我们研究了内耳毛细胞的机电物理学模型，以了解为什么一个人在区分音乐声音方面可能具有生理上的优势。该模型的一个关键特征是，我们避免了采用“黑箱”系统类型的方法。所有参数都是明确定义的物理量，包括膜厚度、弯曲模量、机电特性和几何特征等。我们使用双音干扰问题作为音乐感知的代理，我们的模型允许我们建立探索外部因素（如药物或环境）影响的基础。作为我们获得的见解的一个例子，我们得出结论，细胞膜弯曲模量的降低（例如，可能是由于使用了某一类止痛药）或毛细胞膜的挠曲电效应的增加，会干扰对双音激励的感知。
