Auditory Scene Analysis and Temporal Cortical Computations

听觉场景分析和颞叶皮层计算

• 批准号: 9013468
• 负责人: Jonathan Z. Simon
• 金额: $ 30.86万
• 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/9013468
• 关键词: Acoustics; Address; Aging; Area; Attention; Auditory; Auditory area; Brain; Cereals; Cochlear Implants; Complex; Conflict (Psychology); Crowding; Cues; Disease; Ear; Elements; Environment; Failure; Future; Health; Hearing; Human; Impairment; Individual; Lead; Left; Link; Location; Magnetoencephalography; Measures; Modeling; 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 stimulus; base; design; hearing impairment; human subject; insight; interest; neuroimaging; neuromechanism; programs; relating to nervous system; research study; 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个极其困难的数学问题，但我们的大脑通常会完成这项任务，而且通常不需要付出什么明显的努力。然而，这项艰巨任务的神经基础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，我们不知道神经处理的哪些特定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，这项拟议的研究使用脑磁图（MEG）来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，使我们能够推断这些声音的神经表征。这些神经表征是时间性的：神经处理随着持续的声学动态而及时展开。该研究计划将使用这些时间表示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听觉皮层不同区域中分离的各个声源，并特别强调语音。它的总体假设是听觉皮层采用一种通用的神经编码方案，本质上是真正的时间性的，它不仅是一般听觉处理的基础，也是听觉场景分离的基础。第一个具体目标将确定听觉皮层如何在困难的听力情况下神经表示语音。一个例子是混响环境中噪声中的语音，这是一种非常相关的组合，会严重损害语音清晰度。另一个例子是在几个相互竞争的发言者在场的情况下聆听一个发言者的讲话。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。第二个具体目标将确定动态非语音的这些神经语音表示的类似物，特别是当声音是较大声学场景的单独组成部分时。这会将关于语音隔离的已知信息推广到更广泛的声音类别（虽然语音对于人类听众非常重要，但大多数声音不是语音）。第三个具体目标是研究听觉皮层在复杂声学场景中识别和隔离单个说话者的详细神经机制。音调和音色是已知对此任务很重要的两种声学线索，它们被单独且独立地修改，以便可以确定它们对语音听觉场景分离的神经过程的各自贡献。