Auditory Scene Analysis and Temporal Cortical Computations

听觉场景分析和颞叶皮层计算

• 批准号: 9440408
• 负责人: Jonathan Z. Simon
• 金额: $ 31.06万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-03-01 至 2020-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9440408
• 关键词: Acoustics; Address; Aging; Area; Attention; Auditory; Auditory area; Brain; Cochlear Implants; Complex; Conflict (Psychology); Crowding; Cues; Disease; Ear; Elements; Environment; Failure; Future; Grain; Hearing; Human; Impairment; Individual; Lead; Link; Location; Magnetoencephalography; Mathematics; Measures; Nature; Noise; Outcome; Presbycusis; Process; Research; Resolution; Rest; Restaurants; Role; Scheme; Sorting - Cell Movement; Source; Speech; Speech Disorders; Speech Intelligibility; Stimulus; Stream; Structure; Testing; Time; Translational Research; Voice; analog; auditory processing; auditory stimulus; design; experimental study; hearing impairment; human subject; insight; interest; neuroimaging; neuromechanism; programs; public health relevance; relating to nervous system; response; segregation; social; sound; temporal measurement; tool

 DESCRIPTION (provided by applicant): When many people in a room are talking at the same time, the sounds of their voices mix with each other before ever arriving at our ears. Despite the fact that sorting out this sound mixture into individual voices is a profoundly difficult mathematical problem, our brain routinely accomplishes this task, and often with little apparent effort. The neural underpinnings of this nonetheless difficult task are not at all well understood. Furthermore, when this ability declines, e.g., due to hearing loss or aging, it is not known which specific mechanisms of the neural processing are the most critical in preserving remaining aspects of this ability. In order to address these issues, this proposed research uses magnetoencephalography (MEG) to record from the auditory cortex of behaving human subjects, specifically the temporally dynamic neural responses to individual sound elements and their mixtures. Linking the neural responses with their auditory stimuli and attentional state allows us to infer neural representations of these sounds. These neural representations are temporal: the neural processing unfolds in time in response to the ongoing acoustic dynamics. This research program will use these temporal representations to investigate how complex auditory scenes are neurally encoded, from the broad mixture of the entire acoustic scene to separated individual sources, in different areas of auditory cortex, and with a special emphasis on speech. Its overarching hypothesis is that auditory cortex employs a universal neural encoding scheme, genuinely temporal in nature, which underlies not only general auditory processing but also auditory scene segregation. The first specific aim will determine how auditory cortex neurally represents speech in difficult listening situations. One example is of speech in noise in a reverberant environment, a very relevant combination which can strongly undermine speech intelligibility. Another example is listening to a speaker in the presence of several competing speakers. In this case, understanding how the background (the mixture of the competing speakers) is neurally represented is of particular interest, and of direct relevance in determining how the brain segregates the foreground speech from the background. The second specific aim will determine analogs of these neural speech representations for dynamic non-speech sounds, especially when the sounds are separate components of a larger acoustic scene. This will generalize what is known about speech segregation to a wider class of sounds (while speech is very important for human listeners, most sounds are not speech). The third specific aim investigates the detailed neural mechanisms by which auditory cortex identifies and isolates individual speakers in a complex acoustic scene. Pitch and timbre, two acoustic cues known to be important for this task, are separately and independently modified, so that their individual contributions to the neural process of auditory scene segregation of speech may be determined.

 描述（由申请人提供）：当一个房间里有很多人同时说话时，他们的声音在到达我们耳朵之前就会相互混合，尽管将这种声音混合物分类为单独的声音是一件很困难的事情。尽管这是一个极其困难的数学问题，但我们的大脑通常会毫不费力地完成这项任务，但这项艰巨任务的神经基础却尚未得到很好的理解。 此外，当这种能力下降时，例如由于听力损失或衰老，不知道哪种特定的神经处理机制对于保留这种能力的其余方面最关键。为了解决这些问题，本提议的研究使用了这种方法。脑磁图（MEG）记录行为人类受试者的听觉皮层，特别是对单个声音元素及其混合物的时间动态神经反应，将神经反应与其听觉刺激和注意力状态联系起来，使我们能够推断出这些声音的神经表征。这些神经表征是时间性的：神经系统根据持续的声学动态进行及时展开处理，该研究项目将使用这些时间性表征来研究如何对复杂的听觉场景进行神经编码，从整个声学场景的广泛混合到声音。其总体假设是听觉皮层采用一种通用的神经编码方案，本质上是纯粹的时间性，这不仅是一般听觉处理的基础，也是听觉场景分离的基础。 .第一具体目标将决定听觉皮层如何在困难的聆听情况下神经表示语音。一个例子是混响环境中的噪声中的语音，这是一种非常相关的组合，会严重损害语音的清晰度。另一个例子是在多个竞争者存在的情况下聆听讲话者的声音。在这种情况下，了解背景（竞争说话者的混合）如何在神经上表示是特别令人感兴趣的，并且与确定大脑如何将前景语音与背景分离有直接关系。这些神经语言的动态非语音声音的表示，特别是当声音是较大声学场景的单独组成部分时，这会将有关语音隔离的知识概括为更广泛的声音类别（虽然语音对于人类听众非常重要，但大多数声音并不重要。第三个具体目标是研究听觉皮层在复杂的声学场景中识别和隔离单个说话者的详细神经机制，这两个已知的声学线索对于这项任务很重要，并且是单独和独立修改的。他们对神经系统的个人贡献可以确定语音的听觉场景分离过程。