DEVELOPING AND TESTING MODELS OF THE AUDITORY SYSTEM WITH & WITHOUT HEARING LOSS

开发和测试听觉系统模型

• 批准号: 8040374
• 负责人: Laurel H. Carney
• 金额: $ 32.65万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-12-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8040374
• 关键词: Acoustic Nerve; Attention; Auditory; Auditory system; Brain; Brain Stem; Cochlear nucleus; Code; Complex; Computer Simulation; Cues; Data; Dependence; Detection; Development; Environment; Freezing; Frequencies; Goals; Hearing; Hearing Aids; Human; Individual; Inferior Colliculus; Knowledge; Literature; Masks; Midbrain structure; Modeling; Nerve Fibers; Neurons; Noise; Olives - dietary; Oryctolagus cuniculus; Pattern; Performance; Peripheral; Physiological; Population; Process; Psychophysiology; Reporting; Research; Sensorineural Hearing Loss; Signal Transduction; Staging; Stimulus; Structure; Synapses; Test Result; Testing; Time; auditory pathway; awake; base; computerized data processing; coping; design; experience; hearing impairment; improved; insight; neural circuit; neuromechanism; novel; programs; public health relevance; relating to nervous system; response; sound; tool; tool development

DESCRIPTION (provided by applicant): The most common problem reported by people with sensorineural hearing loss is listening in the presence of background noise. The new efforts presented in this proposal will focus on the development, testing, and application of a composite computational model for physiological and psychophysical responses to complex sounds, especially sounds in the presence of background noise. A model that explains both the impressive ability of normal-hearing listeners, and the difficulty of listeners with hearing loss, to hear sounds in noisy environments will be an invaluable tool to better understand and predict listeners' performance in difficult auditory situations. This information can then be used to design new and improved hearing-aid signal-processing strategies that are successful in noisy situations. Previous computational models have successfully described auditory processing at several levels of the auditory system with phenomenological models for the auditory periphery that include cochlear tuning, transduction, and discharge times of individual auditory-nerve fibers. More recent models describe single neurons and neural circuits in the brain stem and mid-brain, including binaural interactions and neural amplitude-modulation processing. Computational models of neural population responses have also been developed to predict the performance of listeners with and without hearing loss in basic psychophysical tasks. In the proposed project, experience with these models will be leveraged to develop a novel, composite model that ties together these different levels of processing, providing a tool for studying the interactions of stimulus cues and neural mechanisms along the auditory pathway. This computational model for monaural and binaural processing of complex sounds will be tested and refined using physiological recordings from the midbrain (inferior colliculus) of awake rabbit and psychophysical tests in human listeners. The model will be used to predict existing psychophysical data for masked detection, both with and without binaural cues, by listeners with normal hearing. These psychophysical studies will be extended to include listeners with sensorineural hearing loss. Finally, the new model will predict performance of listeners with and without hearing loss on a masked amplitude-modulation (AM) detection task using reproducible modulation maskers. Physiological tuning for amplitude-modulation frequency first emerges at the level of the midbrain, the highest level of the proposed model. Thus this task will allow direct comparison between physiological aspects of AM processing at the mid-brain and psychophysical performance. This proposal provides a systematic transition from modeling basic physiological responses to predicting performance of listeners with and without hearing loss in psychophysical detection tasks in the audio- and modulation-frequency domains. The long term goal of this research program is to develop a robust tool for the development and testing of novel signal-processing strategies for listeners with hearing loss. PUBLIC HEALTH RELEVANCE: The Public Health Relevance of this project is to develop a better understanding of the difficulties in noisy situations for listeners with hearing loss. We will build a computational model for the auditory system of listeners with and without sensorineural hearing loss. This model will be used to predict performance of listeners for detection in noisy situations. Because hearing loss typically involves difficulty understanding complex sounds, especially in noise, knowledge of how the healthy brain copes with difficult listening environments will provide new and important insights for aiding listeners with hearing loss.

描述(申请人提供)：感觉神经性听力损失患者报告的最常见问题是在背景噪声存在的情况下听力。本提案中提出的新努力将侧重于开发、测试和应用复杂声音，特别是存在背景噪声的声音的生理和心理物理反应的复合计算模型。一个模型既可以解释听力正常的听众令人印象深刻的能力，也可以解释听力损失的听众在嘈杂环境中听到声音的困难，这将是更好地理解和预测听众在困难听觉情况下表现的宝贵工具。然后，这些信息可以用来设计新的和改进的助听器信号处理策略，这些策略在嘈杂的情况下是成功的。以前的计算模型已经成功地描述了听觉系统的多个水平的听觉处理，其中听觉外围的现象学模型包括耳蜗调谐、转导和单个听神经纤维的放电时间。最近的模型描述了脑干和中脑中的单个神经元和神经回路，包括双耳相互作用和神经幅度调制处理。神经群体反应的计算模型也被用来预测有听力损失和没有听力损失的听者在基本心理物理任务中的表现。在拟议的项目中，将利用这些模型的经验来开发一种新颖的复合模型，将这些不同水平的处理联系在一起，为研究刺激线索和听觉通路上的神经机制的相互作用提供一个工具。这种单耳和双耳处理复杂声音的计算模型将使用清醒兔的中脑(下丘)的生理录音和人类听者的心理物理测试来测试和改进。该模型将用于预测现有的心理物理数据，以供听力正常的听者在有或没有双耳线索的情况下进行掩蔽检测。这些心理物理研究将扩大到包括感音神经性听力损失的听众。最后，新的模型将使用可重复的调制掩蔽来预测有听力损失和没有听力损失的听者在掩蔽幅度调制(AM)检测任务中的表现。调幅频率的生理调谐首先出现在中脑水平，这是所提出的模型的最高水平。因此，这项任务将允许在中脑AM处理的生理方面与心理物理表现之间进行直接比较。这一建议提供了一个系统的过渡，从模拟基本的生理反应到预测有听力损失和没有听力损失的听者在音频和调制频率域的心理物理检测任务中的表现。这项研究计划的长期目标是开发一种强大的工具，为听力损失的听众开发和测试新的信号处理策略。 公共卫生相关性：该项目的公共卫生相关性是为了更好地了解听力损失听众在嘈杂环境中遇到的困难。我们将为有和没有感音神经性听力损失的听者的听觉系统建立一个计算模型。该模型将被用来预测监听者在噪声环境下的检测性能。由于听力损失通常涉及难以理解复杂的声音，特别是在噪音中，了解健康的大脑如何应对困难的听力环境将为帮助听力损失的听者提供新的重要见解。