Cocktail Party Problem: Perspective on Neurobiology of Auditory Scene Analysis

鸡尾酒会问题：听觉场景分析的神经生物学视角

• 批准号: 8078866
• 负责人: Mounya Elhilali
• 金额: $ 44.48万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8078866
• 关键词: Acoustics; Animal Model; Animals; Area; Attention; Auditory; Auditory area; Auditory system; Beryllium; Binding; Cherry - dietary; Child; Cochlear Implants; Cognitive; Complex; Computer Simulation; Computer Systems; Engineering; Environment; Face; Feedback; Goals; Hearing Aids; Human; Investigation; Knowledge; Magnetoencephalography; Maps; Mediating; Medical; Methods; Military Personnel; Modeling; Nature; Neurobiology; Neurons; Noise; Physiological; Play; Population; Prefrontal Cortex; Process; Psychoacoustics; Psychophysiology; Research; Robotics; Role; Science; Sensory; Speech; Staging; Stream; System; Techniques; Technology; Testing; User-Computer Interface; aging brain; auditory pathway; awake; base; communication aid; computer framework; design; expectation; experience; human subject; improved; infancy; neural circuit; neuromechanism; normal aging; novel; public health relevance; relating to nervous system; research study; segregation; sound; theories

DESCRIPTION (provided by applicant): A Multi-scale Perspective on the Neurobiology of Auditory Scene Analysis A. Aims and Significance Despite the enormous advances in computing technology over the last decades, there are stills many tasks that are easy for a child, yet difficult for advanced computer systems. A particular challenge to most existing systems is dealing with complex acoustic environments, background noises and competing talkers: A challenge often experienced in cocktail parties (Cherry, 1953) and formally referred to as auditory scene analysis (Bregman, 1990). Progress in this field has tremendous implications and long- term benefits covering the medical, industrial, military and robotics domains; as well as improving communication aids (hearing aids, cochlear implants, speech-based human-computer interfaces) for the sensory-impaired and aging brains. Despite its importance for both engineering and perceptual sciences, the study of the neural underpinnings of auditory scene analysis remains in its infancy. This field is particularly challenged by the lack of integrative theories which incorporate our knowledge of the perceptual bases of scene analysis with the neural mechanisms along various stages of the auditory pathway. Because of the nature of the problem, the neural circuitry at play is intricate and multi-scale by design. The objective of the proposed research is to provide a systems view to modeling scene analysis which integrates mechanisms at the single neuron level, population level and across area interactions. The intellectual merit of the proposed theory is to elucidate the specific mechanisms and computational rules at play; facilitate its integration in engineering systems and enable generating novel testable predictions. The proposal investigates the key hypothesis that attention to a feature of a complex sound instantiates all elements that are coherent with this feature, thus binding them together as one perceptual "object" or stream. This "binding hypothesis" requires three scales of analyses: a micro-level mapping of complex sounds into a multidimensional cortical feature representation; a meso-level coherence analysis correlating activity in populations of cortical neurons; and macro-level feedback processes of attention and expectations that mediate auditory object formation. We shall formulate this hypothesis within a multi-scale computational framework that provides a unified theory for the neural underpinnings of auditory scene analysis. The three core research aims of this project explore all facets of this model employing computational and physiological approaches: Aim I. A multi-scale coherence model: The main goal is to formulate the "binding hypothesis" as a unified biologically plausible theory of auditory streaming, integrating multi-scale sensory with cognitive cortical mechanisms. This computational effort will incorporate findings from experiments in Aims II and III, generate testable predictions, as well as provide effective algorithmic implementations to tackle the "cocktail party problem" in biomedical applications; Aim II. Physiological investigations of the multi-scale coherence theory: Our aim is to use an animal model to record single-unit (micro-level, meso-level) and across area (macro-level) physiological activity in both primary auditory and prefrontal cortex, while presenting sufficiently complex acoustic environments so as to test and refine the computational model; Aim III. Refinement of the coherence theory with physiological and perceptual testing in humans: The objective is to directly test predictions from the model in human subjects, using magnetoencephalography (MEG) and psychoacoustic experiments. We shall particularly focus on the role of cortical mechanisms in scene analysis in normal and aging brains. The proposed research draws upon the expertise of a cross-disciplinary team integrating neurobiology and engineering. It is unique in that it is the first effort to postulate a role for coherence in the scene analysis problem, and to investigate the "binding hypothesis" integrating cortical and attention mechanisms in auditory streaming experiments. In addition, by testing the theory directly on human subjects and comparing normal and aging brains (known to face perceptual difficulties in cocktail party settings), we hope to better understand the neural underpinnings of scene analysis under their normal and malfunctioning states, hence enhancing the translational potential of the model. The broader impact of this effort is to provide versatile and tractable models of auditory stream segregation, significantly facilitating the integration of such capabilities in engineering systems. PUBLIC HEALTH RELEVANCE: A Multi-scale Perspective on the Neurobiology of Auditory Scene Analysis Project Relevance: The question of how complex acoustic scenes are parsed by the auditory system into auditory objects and streams is one of the most fundamental questions in perceptual science. Despite its importance, the study of its underlying neural mechanisms remains in its infancy. We believe that significant progress in this area can be achieved by combining sophisticated computational modeling and psychophysical techniques with recently available methods for neural recording from awake behaving animals in interdisciplinary efforts, such as the one described in this proposal. In addition, by testing the theory directly on human subjects and comparing normal and aging brains (known to face perceptual difficulties in cocktail party settings), we hope to better understand the neural underpinnings of scene analysis under their normal and malfunctioning states, hence enhancing the translational potential of the model. The broader impact of this effort is to provide versatile and tractable models of auditory stream segregation, significantly facilitating the integration of such capabilities in engineering systems; as well as improving communication aids (hearing aids, cochlear implants, speech-based human-computer interfaces) for the sensory-impaired and aging brains.

描述（由申请人提供）：听觉场景分析神经生物学的多尺度视角 A. 目标和意义 尽管过去几十年来计算技术取得了巨大进步，但仍然有许多任务对儿童来说很容易，但也很困难用于先进的计算机系统。大多数现有系统面临的一个特殊挑战是处理复杂的声学环境、背景噪音和竞争的谈话者：鸡尾酒会中经常遇到的挑战（Cherry，1953），正式称为听觉场景分析（Bregman，1990）。该领域的进展对医疗、工业、军事和机器人领域具有巨大影响和长期利益；以及为感觉受损和老化的大脑改进沟通辅助工具（助听器、人工耳蜗、基于语音的人机界面）。 尽管听觉场景分析的神经基础对工程和感知科学都很重要，但它的研究仍处于起步阶段。该领域尤其面临着缺乏整合理论的挑战，这些理论将我们对场景分析的感知基础的知识与听觉通路各个阶段的神经机制相结合。由于问题的性质，起作用的神经回路在设计上是复杂且多尺度的。所提出的研究的目的是提供一个系统视图来建模场景分析，它集成了单神经元级别、群体级别和跨区域交互的机制。该理论的智力价值在于阐明了具体的机制和计算规则；促进其在工程系统中的集成并能够生成新颖的可测试预测。 该提案研究了一个关键假设，即对复杂声音特征的关注会实例化与该特征相关的所有元素，从而将它们绑定在一起作为一个感知“对象”或流。这种“约束假设”需要三个层面的分析：复杂声音到多维皮质特征表示的微观层面映射；与皮质神经元群体活动相关的中观水平一致性分析；介导听觉对象形成的注意力和期望的宏观反馈过程。 我们将在多尺度计算框架内制定这一假设，为听觉场景分析的神经基础提供统一的理论。该项目的三个核心研究目标采用计算和生理学方法探索该模型的所有方面： 目标 I. 多尺度一致性模型：主要目标是将“结合假设”制定为统一的听觉流生物学合理理论，将多尺度感觉与认知皮层机制相结合。这项计算工作将结合 Aims II 和 III 中的实验结果，生成可测试的预测，并提供有效的算法实现来解决生物医学应用中的“鸡尾酒会问题”； 目标二。多尺度一致性理论的生理学研究：我们的目标是利用动物模型记录初级听觉皮层和前额皮质的单单位（微观水平、中观水平）和跨区域（宏观水平）生理活动，同时呈现足够复杂的声学环境，以便测试和完善计算模型； 目标三。通过人类生理和感知测试来完善一致性理论：目标是使用脑磁图 (MEG) 和心理声学实验直接测试人类受试者模型的预测。我们将特别关注皮质机制在正常和衰老大脑场景分析中的作用。 拟议的研究利用了整合神经生物学和工程学的跨学科团队的专业知识。它的独特之处在于，它是首次尝试假设场景分析问题中的连贯性的作用，并研究在听觉流实验中整合皮质和注意机制的“绑定假设”。此外，通过直接在人类受试者上测试该理论并比较正常和衰老的大脑（已知在鸡尾酒会环境中面临感知困难），我们希望更好地理解正常和故障状态下场景分析的神经基础，从而增强模型的转化潜力。这项工作的更广泛影响是提供通用且易于处理的听觉流分离模型，显着促进此类功能在工程系统中的集成。 公共卫生相关性：听觉场景分析神经生物学的多尺度视角 项目相关性：听觉系统如何将复杂的声学场景解析为听觉对象和流的问题是感知科学中最基本的问题之一。尽管它很重要，但对其潜在神经机制的研究仍处于起步阶段。我们相信，通过将复杂的计算模型和心理物理学技术与跨学科努力中最近可用的清醒行为动物神经记录方法相结合，可以在这一领域取得重大进展，例如本提案中描述的方法。此外，通过直接在人类受试者上测试该理论并比较正常和衰老的大脑（已知在鸡尾酒会环境中面临感知困难），我们希望更好地理解正常和故障状态下场景分析的神经基础，从而增强模型的转化潜力。这项工作的更广泛影响是提供通用且易于处理的听觉流分离模型，显着促进此类功能在工程系统中的集成；以及为感觉受损和老化的大脑改进沟通辅助工具（助听器、人工耳蜗、基于语音的人机界面）。