Cocktail Party Problem: Perspective on Neurobiology of Auditory Scene Analysis

描述(由申请人提供)：听觉场景分析的神经生物学的多尺度视角A.目的和意义尽管在过去的几十年里，计算机技术取得了巨大的进步，但仍然有许多任务对孩子来说很容易，但对先进的计算机系统来说却是困难的。对大多数现有系统来说，一个特别的挑战是处理复杂的声学环境、背景噪音和相互竞争的说话者：这一挑战在鸡尾酒会上经常遇到(Cherry，1953)，正式称为听觉场景分析(Bregman，1990)。这一领域的进展具有巨大的影响和长期的好处，涵盖医疗、工业、军事和机器人领域；以及为感觉受损和老化的大脑改进通信辅助设备(助听器、人工耳蜗植入物、基于语音的人机界面)。尽管它对工程学和感知科学都很重要，但对听觉场景分析的神经基础的研究仍处于初级阶段。这一领域尤其受到缺乏综合理论的挑战，这些理论将我们对场景分析的知觉基础的知识与听觉通路不同阶段的神经机制结合在一起。由于问题的性质，所起作用的神经电路在设计上是复杂和多尺度的。这项研究的目的是提供一个系统的视角来建模场景分析，它集成了单个神经元水平、群体水平和跨区域相互作用的机制。提出的理论的智力价值是阐明具体的机制和计算规则发挥作用；促进其在工程系统中的集成，并能够产生新的可测试的预测。该方案研究了一个关键假设，即对复杂声音的一个特征的注意实例化了与该特征相一致的所有元素，从而将它们绑定在一起，作为一个知觉“对象”或流。这一“束缚假说”需要三个尺度的分析：将复杂声音映射到多维皮质特征表征的微观层面；将皮层神经元群体中的活动关联起来的中观层面的连贯分析；以及调节听觉对象形成的注意力和预期的宏观层面反馈过程。我们将在一个多尺度的计算框架内阐述这一假设，为听觉场景分析的神经基础提供一个统一的理论。本项目的三个核心研究目标是利用计算和生理学方法探索该模型的各个方面：目的一、多尺度一致性模型：主要目标是将多尺度感觉和认知皮质机制结合起来，形成一个统一的生物学上可信的听觉流传输理论。这项计算工作将纳入AIMS II和III的实验结果，产生可测试的预测，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”；AIM II.多尺度一致性理论的生理学研究：我们的目标是使用动物模型来记录初级听觉和前额叶皮质的单个单位(微观水平、中观水平)和跨区域(宏观水平)的生理活动，同时呈现足够复杂的声学环境，以便测试和改进计算模型；目的III.在人体内进行生理和知觉测试的一致性理论的改进：目标是使用脑磁图(MEG)和心理声学实验，在人类受试者中直接测试该模型的预测。我们将特别关注皮层机制在正常和老化大脑的场景分析中的作用。这项拟议的研究利用了一个整合了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，这是第一次尝试假设连贯在场景分析问题中的作用，并在听觉流传输实验中研究了整合皮层和注意机制的约束假说。此外，通过直接在人类受试者身上测试该理论，并比较正常和老化的大脑(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场景分析在正常和故障状态下的神经基础，从而增强该模型的翻译潜力。这一努力的更广泛影响是提供通用和易处理的听觉流分离模型，显著促进工程系统中此类能力的集成。

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.