AUDITORY PROCESSING OF COMPLEX SOUNDS

描述（由申请人提供）：如果不详细了解对声音的生理反应，就无法理解听觉感知的神经机制，而对声音的心理物理反应已经有了很好的描述。该建议提出了一个全面的方法来解决这个重要的问题，并侧重于复杂声音的振幅调制所携带的信息是如何被大脑编码和处理的问题。尽管数字助听器技术最近取得了进展，但我们对处理复杂声音的神经机制的有限理解仍然是我们帮助听力损失听众的能力的一个重大限制。新的策略，以帮助听众处理声音在复杂的声学环境中将出现从我们的调查如何健康的听觉系统处理这一挑战。该提案的三个目标具有行为，生理和计算建模方法的新颖组合，以解决编码和处理调幅（AM）声音的问题。第一个目标将测试关于行为和心理物理阈值的三个假设。第一个假设侧重于定义兔子和人类的AM检测和辨别阈值，并使用与生理方法兼容的严格匹配的测试程序（目标2）。第二个假设探讨了一个长期存在的难题：行为AM检测阈值随着声级的增加而提高，而单单位生理编码（基于当前理论）随着声级的增加而降低。第三个假设涉及掩蔽AM检测的详细线索的识别。这些线索将被确定与调制域中的可再现掩蔽的新应用。第二个目标是在清醒家兔下丘水平上验证生理性AM编码的假设。这些研究将包括根据目标1的行为结果选择的刺激。我们已经开发了新的生理方法，从IC神经元群体使用四极的时间精确记录。这些记录使得能够严格测试神经编码对平均放电速率和时间响应模式的相对依赖性，包括对神经元集合的尖峰速率和模式的统计分析。第三个目标使用计算技术来测试竞争理论的AM速率调整的IC。最近的模型提出了各种神经机制来解释中脑的AM反应。我们将严格测试这些模型，并将包括测试与刺激以外的那些模型的设计。结果将明确确定哪些模型与我们的生理数据最一致。这些研究将促进我们对听觉系统AM编码和加工机制的理解。这些信息将指导通过改进助听器信号处理算法来增强和恢复听力损失听众复杂声音的关键方面。该项目的公共卫生相关性是确定健康的听觉系统如何编码复杂的声音。我们将使用行为，生理和计算机建模方法的新组合来识别大脑如何编码和提取复杂声音中的振幅波动。由于人类的听力损失通常涉及难以理解复杂的声音，因此了解大脑如何编码这些无处不在的声音将为帮助听力损失的听众提供新的重要见解。

DESCRIPTION (provided by applicant): The neural mechanisms of auditory perception cannot be understood without detailed knowledge of physiological responses to sounds for which psychophysical responses are well described. This proposal presents a comprehensive approach to this important problem and focuses on the question of how information carried by amplitude modulations of complex sounds is encoded and processed by the brain. Despite recent advances in digital hearing-aid technology, our limited understanding of the neural mechanisms involved in processing complex sounds remains a significant limitation in our ability to aid listeners with hearing loss. New strategies to assist listeners with processing sounds in complex acoustic environments will emerge from our investigations of how the healthy auditory system handles this challenge. The three Aims of this proposal feature a novel combination of behavioral, physiological, and computational modeling approaches to address the problem of encoding and processing amplitude-modulated (AM) sounds. The 1st Aim will test three hypotheses concerning behavioral and psychophysical thresholds. The first hypothesis focuses on defining AM detection and discrimination thresholds for rabbits and humans and uses rigorously matched test procedures that are compatible with physiological approaches (Aim 2). The second hypothesis probes a long-standing puzzle: behavioral AM-detection thresholds improve as sound level increases, whereas single-unit physiological coding (based on current theories) degrades as level increases. The third hypothesis concerns the identification of detailed cues for masked AM detection. These cues will be identified with a novel application of reproducible maskers in the modulation domain. The 2nd Aim will test hypotheses of physiological AM coding at the level of the inferior colliculus (IC) in awake rabbit. These studies will include stimuli selected on the basis of behavioral results from Aim 1. We have developed new physiological methods for temporally precise recordings from populations of IC neurons using tetrodes. These recordings enable rigorous tests of the relative reliance of neural encoding on average discharge rates and temporal response patterns, including statistical analyses of spike rates and patterns across ensembles of neurons. The 3rd Aim uses computational techniques to test competing theories for AM-rate tuning in the IC. Recent models have proposed various neural mechanisms to explain AM responses in the midbrain. We will rigorously test these models and will include tests with stimuli other than those for which the models were designed. The results will explicitly determine which models are most consistent with our physiological data. These studies will advance our understanding of the mechanisms underlying AM coding and processing in the auditory system. This information will instruct efforts to enhance and restore critical aspects of complex sounds for listeners with hearing loss by improving hearing-aid signal-processing algorithms. The Public Health Relevance of this project is to determine how the healthy auditory system encodes complex sounds. We will use a novel combination of behavioral, physiological, and computer modeling approaches to identify how the brain encodes and extracts amplitude fluctuations in complex sounds. Because hearing loss in humans typically involves difficulty understanding complex sounds, knowledge of how the brain codes these ubiquitous sounds will provide new and important insights for aiding listeners with hearing loss.