US-French Collaboration: Auditory computations for interpreting and producing communication signals.

美法合作：用于解释和产生通信信号的听觉计算。

• 批准号: 1311446
• 负责人: Frederic Theunissen
• 金额: $ 71.88万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1311446&HistoricalAwards=false
• 关键词: US; French; Collaboration; Auditory; computations

Human speech and animal communication require both the extraction of meaning from sound and the processing of one's own voice to guide the production of these vocalizations. These processes require non-trivial computations that have challenged linguists and engineers but that are performed effortlessly by our brains. To understand what are the neural computations performed to decode the behavioral meaning and vocal gestures of communication signals, this study will examine how the auditory cortex of a songbird processes the complete vocal repertoire of its own species. The Theunissen Lab acquired a unique database of all the vocalizations emitted by adult and juvenile, and both male and female zebra finches. This database contains the complete repertoire with multiple exemplars of each vocalization type for many individuals. Because the behavioral context of each communication sound was carefully recorded, these sounds are classified in meaning categories. This database will thus enable the detailed investigation of how the auditory system extract meaning from vocalizations, while controlling for variability of production within vocalization type as well as between individuals.The approach of this project consists in obtaining neural responses to these communication sounds using advanced neurophysiological recording techniques, and then investigating the neural computations by finding the statistics models that best predict these responses. Multi-electrode arrays will be used to record the simultaneous neural activity of large sets of single neurons in the primary and secondary auditory areas. The response of these neurons will then be fitted using statistical models that incorporate increasing levels of abstraction: from elementary sound features, to vocal gestures and semantic labels. The representation in terms of vocal gestures will be obtained from a reduced physical model of the avian vocal organ. This analysis will not only point out the brain regions that are involved in semantic processing but also the nature of the hierarchical computations that lead to these higher-level representations. The research will also investigate the link between perception and production by directly assessing the role of a motor-based representation of sounds in high-level auditory areas. By combining ethological, neurophysiological and computational studies of acoustic communication in a songbird, the project will establish an appropriate animal model system to elucidate how the auditory cortex extracts and categorizes sound features in order to link sound to meaning. Given the similarities in the anatomy and physiology of the auditory system across vertebrates and the common signal processing problems shared in all vocal communications, this study can also contribute significantly to the neurophysiological understanding of neural mechanisms underlying speech perception. This award is being co-funded by NSF's Office of the Director, International Science and Engineering. A companion project is being funded by the French National Research Agency (ANR).

人类语言和动物交流既需要从声音中提取意义，也需要处理自己的声音来指导这些发声的产生。这些过程需要大量的计算，这些计算挑战了语言学家和工程师，但我们的大脑可以毫不费力地完成这些计算。为了理解什么是神经计算来解码交流信号的行为意义和发声手势，这项研究将研究鸣鸟的听觉皮质如何处理它自己物种的完整发声曲目。休尼森实验室获得了一个独特的数据库，其中包括成年和青少年以及雄性和雌性斑马雀发出的所有发声。这个数据库包含完整的曲目，每个发声类型的多个样本供许多人使用。因为每个交流声音的行为语境都被仔细地记录下来，所以这些声音被归类为意义类别。因此，这个数据库将能够详细研究听觉系统如何从发声中提取意义，同时控制发声类型以及个体之间产生的可变性。该项目的方法在于使用先进的神经生理学记录技术获得对这些交流声音的神经反应，然后通过找到最好地预测这些反应的统计模型来研究神经计算。多电极阵列将被用来记录初级和次级听觉区域中大组单个神经元的同时神经活动。然后，这些神经元的反应将使用纳入不断增加的抽象水平的统计模型进行拟合：从基本的声音特征，到声音手势和语义标签。发声手势方面的表示将从鸟类发声器官的简化物理模型中获得。这一分析不仅将指出参与语义处理的大脑区域，而且还将指出导致这些更高级别表示的分层计算的性质。这项研究还将通过直接评估基于运动的声音表征在高级听觉区域中的作用，来调查感知和产生之间的联系。通过结合对鸣禽声音交流的行为学、神经生理学和计算研究，该项目将建立一个合适的动物模型系统，以阐明听觉皮质如何提取声音特征并对其进行分类，以便将声音与意义联系起来。鉴于脊椎动物听觉系统在解剖学和生理学上的相似之处，以及所有语音交流中共同存在的信号处理问题，这项研究也可以为理解言语感知的神经机制做出重大贡献。该奖项由美国国家科学基金会国际科学与工程主任办公室共同资助。法国国家研究机构(ANR)正在资助一个配套项目。