The role of amplitude modulation in perceiving speech and music

幅度调制在感知语音和音乐中的作用

• 批准号: 10360628
• 负责人: Andrew Chang
• 金额: $ 6.76万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10360628
• 关键词: Acoustics; Address; Affect; Algorithms; Alzheimer' s Disease; Aphasia; Auditory; Auditory Perception; Auditory area; Behavioral; Brain; Brain region; Cognition; Communication; Data; Foundations; Frequencies; Functional Magnetic Resonance Imaging; Goals; Human; Judgment; Linguistics; Machine Learning; Magnetoencephalography; Measures; Mind; Music; Noise; Participant; Pathway interactions; Perception; Performance; Periodicity; Persons; Process; Psychophysics; Records; Research; Research Personnel; Role; Series; Signal Transduction; Solid; Speech; Speech Perception; Stimulus; Structure; System; Testing; Work; auditory processing; career; cognitive neuroscience; experimental study; individuals with autism spectrum disorder; insight; neuroimaging; neuromechanism; non-invasive imaging; operation; programs; relating to nervous system; sound; spectral energy; speech processing

Project Summary/Abstract My career goal is to become a leading researcher on cognitive neuroscience, with a special focus on the neural mechanisms underlying auditory perception, including how humans track and perceive the fleeting audi- tory information in speech and music. In this proposal, I outline a research program to investigate the acoustic and neural distinctions between speech and music, two specialized forms of auditory signals that are closely tied to the human mind. Despite our increasingly rich understanding of the perceptual and neural mechanisms for processing speech or music, surprisingly little is known about why and how they are treated as different au- ditory signals by the human mind and brain in the first place. Investigating these distinctions is foundational for a thorough understanding of how acoustic waveforms are transformed into meaningful information. The work will provide a more solid basis for understanding cognition and communication as well as treating people with communicative deficits, such as people with autism, Alzheimer's disease, and aphasia. I hypothesize that the temporal structure reflected in the amplitude modulation (AM) of speech and music signals is a critical distinctive feature for the brain and engages to different processing pathways, as speech and music are known to have distinct AM rates. A series of studies, combining psychophysics, MEG (magne- toencephalography), fMRI (functional magnetic resonance imaging), and machine learning approaches, will use stimuli with AM rates across the modulation frequency ranges of speech and music to address this topic at the computational (the goals), algorithmic (the representations and operations), and implementational (neural mechanism) levels. (1) Does the AM rate of a sound affect whether it will be perceived as speech or music? (2) Does the AM rate of a stimulus optimize speech and music perceptual performance at different frequencies? (3) What are the underlying neural mechanisms and the associated brain regions implementing the differentiation of speech and music? Aim 1 investigates whether the AM rate of a sound conditions it to be processed as speech or music. By manipulating the AM rate of noise-vocoded speech and music recordings, I hypothesize that the sounds with slower or faster AM rates will likely to be perceived as music or speech, respectively, the perceptual judgment will be biased by the higher or lower spectral energy of neural oscillatory activity (meas- ured by MEG) while listening to the sounds, respectively, and the associated brain regions will be revealed by fMRI with machine learning decoding approaches. Aim 2 investigates whether the AM rate of stimuli optimizes speech and music perceptual performances at different rates. I hypothesize that the music perceptual perfor- mance is optimal at slower AM rates while the speech perceptual performance is optimal at faster AM rates, and the neural oscillatory entrainment at lower or higher frequency band has domain-specific function facilitat- ing speech or music perceptual performance.

项目总结/摘要 我的职业目标是成为认知神经科学的主要研究人员，特别关注 听觉感知的神经机制，包括人类如何跟踪和感知稍纵即逝的奥迪， 在语言和音乐中储存信息。在本提案中，我概述了一个研究计划来研究声学 以及语音和音乐之间的神经区别，这两种特殊形式的听觉信号， 与人类思维息息相关。尽管我们对知觉和神经机制的理解越来越丰富， 对于处理语音或音乐，令人惊讶的是，很少有人知道为什么以及如何将它们视为不同的Au。 人类的大脑和思想首先会发出的信息。研究这些区别是 对声波波形如何转换为有意义的信息的透彻理解。工作 将为理解认知和沟通以及对待人与人之间的关系提供更坚实的基础。 沟通障碍，如自闭症，阿尔茨海默病和失语症患者。 我假设，时间结构反映在幅度调制（AM）的讲话和音乐 信号是大脑的一个关键的独特特征，并参与不同的处理途径，如语音 和音乐具有不同的AM速率。一系列的研究，结合心理物理学，脑磁图（magne- 脑电描记术），功能磁共振成像（功能磁共振成像）和机器学习方法，将 在语音和音乐的调制频率范围内使用AM速率的刺激来解决这个问题， 计算（目标）、算法（表示和操作）和实现（神经 机制）水平。(1)声音的AM速率会影响它被感知为语音还是音乐吗？（二） 刺激的AM速率是否优化了不同频率下的语音和音乐感知性能？（三） 什么是潜在的神经机制和相关的大脑区域实现分化 语言和音乐的？目标1研究声音的AM速率是否使其被处理为 演讲或音乐。通过操纵噪声声码语音和音乐录音的AM速率，我假设 具有较慢或较快AM速率的声音可能分别被感知为音乐或语音， 知觉判断将被神经振荡活动的较高或较低的谱能量（meas， 脑磁图），同时听声音，分别和相关的大脑区域将揭示 fMRI与机器学习解码方法。目的2研究刺激的AM速率是否优化 语音和音乐感知性能在不同的速度。我假设音乐知觉的表现- 语音感知性能在较慢的AM速率下是最佳的而语音感知性能在较快的AM速率下是最佳的， 低频或高频的神经振荡夹带具有领域特异性的易化功能， 语音或音乐的感知表现。