Individual Differences Listening in Noise in Clinically Normal-hearing Adults

项目摘要 听力阈值正常的年轻人在日常嘈杂环境中的听力差异很大 环境.许多人在研究中表现得和他们年龄匹配的重听人一样差[Kidd et al.（2002年）的报告。J. Assoc. Res. Otolaryn. 3，107-119]。这种变化挑战了传统的听觉观 听力损失，假设听力图是评估听力的金标准;然而， 变异仍不清楚。现在，我们实验室和其他实验室的新进展保证了理解的进展。 阈值精细结构的测量已经表明，阈值中的宽的个体变化被忽略。 常规听力图[Lee & Long（2012）.听Res. 283，24-32]。决策权重的个体差异， 在心理物理任务中，用来反映听众对不同频率的依赖性， 个体耳朵特有的耳蜗微力学的不规则性[Lee等人（2016），Adv. Exp.医学生物学 894：457-465]。计算模型已经分离出少数在预测中显示出希望的因素 在不同的噪声中目标听力任务中的个体差异[Lutfi等人（2013），J. Acoust.美国社会 134：2160-2170]。而且，曾经被认为没有伤害风险的噪音暴露水平，已经被证明是 导致与毛细胞的突触连接不可逆转地丧失， 小鼠这种病理学不能通过传统的听力测定法检测到，这导致了人们猜测它可能是 在人群中广泛存在，影响在噪声中的听力[Kujawa和Liberman（2009），J. Neurosci. 29（45）：14077-14085]。在这些发展的推动下，这一提议代表了一种新的努力， 临床上听力正常的年轻成年人在噪音中有效听力的能力存在个体差异。它 在方法上与过去的努力有根本的不同。目标是隔离变异的主要来源， 通过精确地确定听众在使用区分目标的信息时的差异来模拟它们的效果 从噪音。这是通过以下方式实现的：（1）制定一个通用的决策模型， 对这些信息的判断，（2）通过试验的logistic回归估计该模型的参数， 试验数据和（3）比较估计值的最大似然观测器， 每项任务的表现。该方法代表了对传统方法的重大进步， 从性能准确性的测量中推断出潜在的过程。具体目标是应用这种方法 （1）确定外周和中枢过程的相对贡献及其相互作用， 差异，（2）从“个人倾听风格”中解释了听众行为的一般模式，（3） 开发低参数计算模型，用于预测不同听力的个体差异 任务预计从这些研究中获得的知识将为努力改善 评估、分类和治疗对许多人来说是一个令人衰弱的问题， 日常噪音

Project Summary Young adults with normal audiometric thresholds vary widely in their ability to listen in everyday noisy environments. Many perform as poorly in studies as their age-matched, hard-of-hearing counterparts [Kidd et al. (2002). J. Assoc. Res. Otolaryn. 3, 107-119]. The variation challenges the conventional view of hearing loss, which assumes the audiogram to be the gold standard for evaluating hearing; however, the causes of the variation remain unclear. Now, new developments in our lab and others promise progress in understanding. Measures of threshold fine structure have shown that wide individual variation in thresholds are missed by the conventional audiogram [Lee & Long (2012). Hear. Res. 283, 24-32]. Individual differences in decision weights, taken to reflect the reliance listeners place on different frequencies in psychophysical tasks, have been linked to irregularities in cochlear micromechanics unique to individual ears [Lee et al. (2016), Adv. Exp. Med. Biol. 894:457-465]. Computational models have isolated a small number of factors that show promise in predicting individual differences across diverse target-in-noise listening tasks [Lutfi et al. (2013), J. Acoust. Soc. Am. 134:2160-2170]. And, levels of noise exposure, once thought to present no risk of harm, have been shown to produce irreversible loss of synaptic connections to hair cells and subsequent degeneration of afferents in mice. The pathology is not detected by conventional audiometry, leading to speculation that it may be widespread in the population, affecting listening in noise [Kujawa and Liberman (2009), J. Neurosci. 29(45):14077–14085]. Sparked by these developments, this proposal represents a new effort to understand individual differences in the ability of young clinically normal-hearing adults to listen effectively in noise. It differs fundamentally from past efforts in approach. The goal is to isolate the primary sources of variation and model their effects by determining precisely how listeners differ in their use of information distinguishing targets from noise. This is achieved by (1) formulating a general decision model relating the listener's trial-by-trial judgments to this information, (2) estimating the parameters of this model by logistic regression of the trial-by- trial data and (3) comparing the estimated values to those of a maximum-likelihood observer that yields best performance for each task. The approach represents a significant advance over conventional methods that infer underlying processes from measures of performance accuracy. Specific aims are to apply this approach to (1) determine the relative contribution of peripheral and central processes and their interaction to individual differences, (2) account for general patterns of listener behavior from `individual listening styles' and (3) develop a low-parameter computational model for predicting individual differences across diverse listening tasks. It is expected that the knowledge gained from these studies will inform efforts that seek to improve the evaluation, classification and treatment of what is a debilitating problem for many, the challenge of listening in everyday noise.