A Modular Approach to Vocal Learning: Disentangling the Diversity of a Complex Behavioral Trait.
A Modular Approach to Vocal Learning: Disentangling the Diversity of a Complex Behavioral Trait.
复制标题
声音学习的模块化方法：理清复杂行为特征的多样性。
DOI：
10.1016/j.neuron.2019.09.036
复制
发表时间：
2019
期刊：
影响因子：
16.2
通讯作者：
Yartsev,MichaelM
中科院分区：
文献类型：
--
作者：
Wirthlin,Morgan;Chang,EdwardF;Knörnschild,Mirjam;Krubitzer,LeahA;Mello,ClaudioV;Miller,CoryT;Pfenning,AndreasR;Vernes,SonjaC;Tchernichovski,Ofer;Yartsev,MichaelM
声乐学习是一种行为特征，其中社会和声学环境塑造了个人的声乐曲目。在过去的一个世纪里，声乐学习的研究在生态学、生理学、神经科学、分子生物学、基因组学和进化的交叉领域取得了进展。然而，尽管这一特征很复杂，但声音学习经常被描述为一种二元特征，物种被分为声音学习者和非声音学习者。因此，研究主要集中在少数几个物种上，这些物种有强有力的声乐学习证据。然而，最近的研究表明，不同分类群的声乐学习能力是连续的。在这里，我们进一步提出声音学习是一种多组分行为表型，由不同但相互关联的模块组成。将声音学习表型离散到其组成模块中，将有助于在更广泛的物种多样性中整合发现，利用每个物种在特定模块或特定特征组合中的优势。这样的比较研究可以提高对发声学习机制和进化起源的理解。我们提出了一套由行为和神经生物学数据支持的初始声乐学习模块，并强调需要使该领域多样化，以解开声乐学习表型的复杂性。
Vocal learning is a behavioral trait in which the social and acoustic environment shapes the vocal repertoire of individuals. Over the past century, the study of vocal learning has progressed at the intersection of ecology, physiology, neuroscience, molecular biology, genomics, and evolution. Yet, despite the complexity of this trait, vocal learning is frequently described as a binary trait, with species being classified as either vocal learners or vocal non-learners. As a result, studies have largely focused on a handful of species for which strong evidence for vocal learning exists. Recent studies, however, suggest a continuum in vocal learning capacity across taxa. Here, we further suggest that vocal learning is a multi-component behavioral phenotype comprised of distinct yet interconnected modules. Discretizing the vocal learning phenotype into its constituent modules would facilitate integration of findings across a wider diversity of species, taking advantage of the ways in which each excels in a particular module, or in a specific combination of features. Such comparative studies can improve understanding of the mechanisms and evolutionary origins of vocal learning. We propose an initial set of vocal learning modules supported by behavioral and neurobiological data and highlight the need for diversifying the field in order to disentangle the complexity of the vocal learning phenotype.