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。许多人在学习中的表现与年龄匹配的重听同龄人一样差 艾尔(2002)。J.Assoc.奥托兰属(Res.)3、107-119]。这种变化对传统的听力观点提出了挑战 听力损失，认为听力图是评估听力的黄金标准；然而，导致听力损失的原因 变异情况仍不清楚。现在，我们实验室和其他实验室的新进展有望在理解方面取得进展。 对阈值精细结构的测量表明，阈值中广泛的个体差异被 常规听力图[Lee&Long(2012)]。听见。决议283，24-32]。决策权重的个体差异， 反映了听者在心理物理任务中对不同频率的依赖 单个耳朵所特有的耳蜗微力学异常[Lee等人。(2016)，Adv.Exp地中海医院。比奥尔。 894：457-465]。计算模型已经分离出了在预测方面有希望的少数因素 不同噪声中目标听音任务的个体差异[Lutfi等人。(2013)，J.Acoust.SoC。上午好。 134：2160-2170]。而且，曾经被认为不会造成伤害的噪音暴露水平，已经被证明是 导致与毛细胞的突触连接不可逆转的丧失和随后的传入变性 老鼠。传统的听力测试无法检测到这种病理，这导致了人们猜测它可能是 在人群中普遍存在，影响在噪音中的听力[Kujawa和Liberman(2009)，J.Neurosci。 29(45)：14077-14085]。在这些发展的推动下，这项提议代表了一种新的努力，以理解 临床听力正常的年轻成年人在噪音中有效听的能力的个体差异。它 在方法上与过去的努力有根本的不同。目标是隔离主要的变异源和 通过准确地确定听众在使用区分目标的信息时的不同之处来模拟他们的效果 从噪音中。这是通过以下方式实现的：(1)制定与听者的逐次尝试相关的一般决策模型 对这一信息的判断，(2)用Logistic回归估计模型的参数。 试验数据以及(3)将估计值与产生最佳结果的最大似然观测者的估计值进行比较 每项任务的性能。该方法与传统方法相比是一个重大进步，传统方法 从绩效精确度的测量中推断潜在流程。具体目标是应用这种方法 以(1)确定外周和中枢过程及其相互作用对个体的相对贡献 不同之处，(2)解释了听者行为的一般模式，而不是‘个别的听风格’和(3) 开发一个低参数的计算模型来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寻求改善 评估、分类和治疗对许多人来说是一个令人衰弱的问题，倾听的挑战 每天都有噪音。

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.