A minimal physics-based model for musical perception.


Journal

Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876

Informations de publication

Date de publication:
31 01 2023
Historique:
entrez: 24 1 2023
pubmed: 25 1 2023
medline: 27 1 2023
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 36693091
doi: 10.1073/pnas.2216146120
pmc: PMC9945942
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2216146120

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Auteurs

Kosar Mozaffari (K)

Department of Mechanical Engineering, University of Houston, Houston, TX 77204.

Fatemeh Ahmadpoor (F)

Department of Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07102.

Qian Deng (Q)

State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi'an Jiaotong University, Xi'an 710049, China.

Pradeep Sharma (P)

Department of Mechanical Engineering, University of Houston, Houston, TX 77204.
Department of Physics, University of Houston, Houston, TX 77204.

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