{"title":"Beat-based dancing to music has evolutionary foundations in advanced vocal learning.","authors":"Aniruddh D Patel","doi":"10.1186/s12868-024-00843-6","DOIUrl":null,"url":null,"abstract":"<p><p>Dancing to music is ancient and widespread in human cultures. While dance shows great cultural diversity, it often involves nonvocal rhythmic movements synchronized to musical beats in a predictive and tempo-flexible manner. To date, the only nonhuman animals known to spontaneously move to music in this way are parrots. This paper proposes that human-parrot similarities in movement to music and in the neurobiology of advanced vocal learning hold clues to the evolutionary foundations of human dance. The proposal draws on recent research on the neurobiology of parrot vocal learning by Jarvis and colleagues and on a recent cortical model for speech motor control by Hickock and colleagues. These two lines of work are synthesized to suggest that gene regulation changes associated with the evolution of a dorsal laryngeal pitch control pathway in ancestral humans fortuitously strengthened auditory-parietal cortical connections that support beat-based rhythmic processing. More generally, the proposal aims to explain how and why the evolution of strong forebrain auditory-motor integration in the service of learned vocal control led to a capacity and proclivity to synchronize nonvocal movements to the beat. The proposal specifies cortical brain pathways implicated in the origins of human beat-based dancing and leads to testable predictions and suggestions for future research.</p>","PeriodicalId":9031,"journal":{"name":"BMC Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11539772/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12868-024-00843-6","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Dancing to music is ancient and widespread in human cultures. While dance shows great cultural diversity, it often involves nonvocal rhythmic movements synchronized to musical beats in a predictive and tempo-flexible manner. To date, the only nonhuman animals known to spontaneously move to music in this way are parrots. This paper proposes that human-parrot similarities in movement to music and in the neurobiology of advanced vocal learning hold clues to the evolutionary foundations of human dance. The proposal draws on recent research on the neurobiology of parrot vocal learning by Jarvis and colleagues and on a recent cortical model for speech motor control by Hickock and colleagues. These two lines of work are synthesized to suggest that gene regulation changes associated with the evolution of a dorsal laryngeal pitch control pathway in ancestral humans fortuitously strengthened auditory-parietal cortical connections that support beat-based rhythmic processing. More generally, the proposal aims to explain how and why the evolution of strong forebrain auditory-motor integration in the service of learned vocal control led to a capacity and proclivity to synchronize nonvocal movements to the beat. The proposal specifies cortical brain pathways implicated in the origins of human beat-based dancing and leads to testable predictions and suggestions for future research.
期刊介绍:
BMC Neuroscience is an open access, peer-reviewed journal that considers articles on all aspects of neuroscience, welcoming studies that provide insight into the molecular, cellular, developmental, genetic and genomic, systems, network, cognitive and behavioral aspects of nervous system function in both health and disease. Both experimental and theoretical studies are within scope, as are studies that describe methodological approaches to monitoring or manipulating nervous system function.