Understanding music and aging through the lens of Bayesian inference

Jiamin Gladys Heng; Jiayi Zhang; Leonardo Bonetti; Wilson Peng Hian Lim; Peter Vuust; Kat Agres; Shen Hsing Annabel Chen

doi:10.1016/j.neubiorev.2024.105768

Understanding music and aging through the lens of Bayesian inference

Jiamin Gladys Heng^*, Jiayi Zhang, Leonardo Bonetti, Wilson Peng Hian Lim, Peter Vuust, Kat Agres, Shen Hsing Annabel Chen^*

^*Corresponding author for this work

Department of Clinical Medicine - Center for Music In the Brain

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Review › Research › peer-review

1 Citation (Scopus)

Abstract

Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.

Original language	English
Article number	105768
Journal	Neuroscience and Biobehavioral Reviews
Volume	163
ISSN	0149-7634
DOIs	https://doi.org/10.1016/j.neubiorev.2024.105768
Publication status	Published - Aug 2024

Keywords

Aging
Bayesian inference
Learning
Music
Predictive coding

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10.1016/j.neubiorev.2024.105768Licence: CC BY

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title = "Understanding music and aging through the lens of Bayesian inference",

abstract = "Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.",

keywords = "Aging, Bayesian inference, Learning, Music, Predictive coding",

author = "Heng, {Jiamin Gladys} and Jiayi Zhang and Leonardo Bonetti and Lim, {Wilson Peng Hian} and Peter Vuust and Kat Agres and Chen, {Shen Hsing Annabel}",

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doi = "10.1016/j.neubiorev.2024.105768",

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volume = "163",

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AU - Heng, Jiamin Gladys

AU - Zhang, Jiayi

AU - Bonetti, Leonardo

AU - Lim, Wilson Peng Hian

AU - Vuust, Peter

AU - Agres, Kat

AU - Chen, Shen Hsing Annabel

PY - 2024/8

Y1 - 2024/8

N2 - Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.

AB - Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.

KW - Aging

KW - Bayesian inference

KW - Learning

KW - Music

KW - Predictive coding

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JO - Neuroscience and Biobehavioral Reviews

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Understanding music and aging through the lens of Bayesian inference

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Keywords

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