Middle age, a key time point for changes in birdsong and human voice.


Journal

Behavioral neuroscience
ISSN: 1939-0084
Titre abrégé: Behav Neurosci
Pays: United States
ID NLM: 8302411

Informations de publication

Date de publication:
Jun 2020
Historique:
pubmed: 13 3 2020
medline: 2 2 2021
entrez: 13 3 2020
Statut: ppublish

Résumé

Voice changes caused by natural aging and neurodegenerative diseases are prevalent in the aging population and diminish quality of life. Most treatments involve behavioral interventions that target the larynx because of a limited understanding of central brain mechanisms. The songbird offers a unique entry point into studying age-related changes in vocalizations because of a well-characterized neural circuitry for song that shares homology to human vocal control areas. Previously we established a translational dictionary for evaluating acoustic features of birdsong in the context of human voice measurements. In the present study, we conduct extensive analyses of birdsongs from young, middle-aged, and old male zebra finches. Our findings show that birdsongs become louder with age, and changes in periodic energy occur at middle age but are transient; songs appear to stabilize in old birds. Furthermore, faster songs are detected in finches at middle age compared with young and old finches. Vocal disorders in humans emerge at middle age, but the underlying brain pathologies are not well identified. The current findings will motivate future investigations using the songbird model to identify possible brain mechanisms involved in human vocal disorders of aging. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Identifiants

pubmed: 32162938
pii: 2020-17200-001
doi: 10.1037/bne0000363
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

208-221

Subventions

Organisme : University of Arizona
Organisme : Undergraduate Biology Research Program

Auteurs

Areen Badwal (A)

Department of Neuroscience.

Mark Borgstrom (M)

University Information Technology Services.

Robin A Samlan (RA)

Department of Speech, Language, and Hearing Sciences.

Julie E Miller (JE)

Department of Neuroscience and Speech.

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Classifications MeSH