Developing and Testing Models of the Auditory System With and Without Hearing Loss

开发和测试有或没有听力损失的听觉系统模型

• 批准号: 10528472
• 负责人: Laurel H. Carney
• 金额: $ 42.27万
• 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: 2010-04-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10528472
• 关键词: Acoustic Nerve; Acoustics; Address; Affect; Anatomy; Auditory; Auditory system; Automobile Driving; Brain; Cells; Central Nervous System; Characteristics; Cochlea; Cochlear Implants; Code; Collection; Complex; Computer Models; Cues; Data; Data Set; Detection; Discrimination; Environment; Feedback; Foundations; Frequencies; Goals; Hearing; Hearing Aids; Human; Inferior Colliculus; Inner Hair Cells; Knowledge; Loudness; Masks; Medial; Midbrain structure; Modeling; Nerve Fibers; Neurons; Noise; Oryctolagus cuniculus; Pattern; Perception; Performance; Peripheral; Phase; Physiological; Physiology; Play; Property; Psychoacoustics; Psychophysics; Research Design; Resolution; Role; Science; Sensorineural Hearing Loss; Shapes; Signal Detection Analysis; Stimulus; Structure; System; Testing; Textbooks; Time; auditory pathway; awake; cellular transduction; coping; density; design; experimental analysis; experimental study; hearing impairment; improved; innovation; insight; interest; neural; normal hearing; novel strategies; predictive modeling; public health relevance; receptive field; response; sound; task analysis; theories

The goal of this proposal is to establish a new model for masked detection and frequency resolution, applicable to listeners with normal hearing and hearing loss, based on realistic physiological response properties. We are developing a new, fundamental framework for neural representations of acoustic stimuli that can predict a wide range of psychoacoustic phenomena. This framework is focused on neural fluctuations of auditory-nerve (AN) fibers, rather than on energy, average rates, or phase-locking to temporal fine structure. Neural fluctuations (NFs) refer to the relatively slow changes over time in AN responses (i.e., changes with rates ranging from 10s to a few 100 Hz). Neural fluctuations in this frequency range are of interest because they strongly excite, or suppress, neurons in the auditory central nervous system. The NF model is based on known nonlinear properties of inner-hair-cell and AN responses, and thus has important implications for interpreting masking results in listeners with sensorineural hearing loss. A representation of masked sounds based on the NF model is an alternative to the commonly accepted excitation-pattern representation provided by the power spectrum model of masking. The NF model successfully describes basic masking thresholds, as well as many experimental paradigms for which the power-spectrum (or energy) model fails. The NF model is not limited to low frequencies, as are models based on phase-locking to temporal fine structure. Here, the NF framework will be applied not only to masking paradigms, but also to stimulus paradigms that focus on frequency resolution, such as discrimination of the fundamental frequency of harmonic complex tones, or detection of increments in profile-analysis stimuli. Current models for the representation of these stimuli rely on a conceptual peripheral filter bank with critical bandwidths, estimated from human masking results using the power spectrum model of masking. Critical bandwidths, assumed to limit the frequency resolution of the auditory representations of complex sounds, are not consistent with known physiology. In contrast, frequency resolution according to the NF model is grounded on physiologically realistic response properties of AN fibers and sensitivity to neural fluctuations observed in the midbrain. Finally, to explain perception based on NF cues across the entire range of audible sound levels, we will extend our AN model to include NF-driven feedback gain control, guided by the known physiology and anatomy of the medial olivocochlear efferent system. The studies proposed here include: i) computational modeling to predict human thresholds, including re-examination of classical datasets that can, and those that cannot, be explained by the power-spectrum model, ii) related physiological studies in the midbrain, where cells are strongly sensitive to fluctuating inputs, and iii) new psychophysical studies designed to challenge the NF model, in listeners with normal hearing and those with sensorineural hearing loss.

该提案的目的是建立一个新的模型，用于掩盖检测和频率分辨率，适用 基于现实的生理反应特性，具有正常听力和听力损失的听众。我们是 为声学刺激的神经表现形式开发一个新的，基本的框架，可以预测广泛的 心理声学现象的范围。该框架的重点是听觉神经的神经波动（an） 纤维，而不是能量，平均速率或时间锁定为时间细结构。神经波动 （NFS）是指响应中随时间变化的相对较慢的变化（即，速率的变化范围为10s 到几100 Hz）。在此频率范围内的神经波动引起了人们的关注，因为它们强烈兴奋或 抑制听觉中枢神经系统中的神经元。 NF模型基于已知的非线性 内发细胞的特性和一个反应，因此对解释掩盖具有重要意义 导致听众听力损失。基于NF模型的蒙版声音表示 是功率谱提供的普遍接受的激发模式表示的替代方案 掩蔽模型。 NF模型成功地描述了基本的掩蔽阈值以及许多 功率光谱（或能量）模型失败的实验范例。 NF模型不限于 低频，基于时间锁定到时间精细结构的模型也是如此。在这里，NF框架将 不仅可以应用于掩盖范例，还应用于刺激范式，以频率分辨率， 例如歧视谐波复杂音调的基本频率，或检测 轮廓分析刺激。当前代表这些刺激的模型依赖于概念的外围 具有关键带宽的过滤库，使用人掩模的结果估算了使用功率谱模型 掩蔽。临界带宽，假定限制了听觉表示的频率分辨率 复杂的声音与已知生理不一致。相反，根据 NF模型基于纤维的生理现实反应特性和对神经的敏感性 在中脑中观察到的波动。最后，根据整个范围内的NF提示解释感知 在听到声音级别中，我们将扩展我们的模型，以包括NF驱动的反馈收益控制，并在 内侧橄榄石传出系统的已知生理和解剖学。这里提出的研究 包括：i）预测人阈值的计算建模，包括重新检查经典数据集 可以通过功率光谱模型来解释的，ii）相关的生理学研究 中脑，其中细胞对波动的输入非常敏感，iii）新的心理学研究 旨在挑战NF模型，在听力正常的听众和有感觉听力的听众中 损失。