The influence of individual differences in brain rhythms on speech perception with and without age-related hearing loss

目前全世界有4.3亿人患有致残性听力损失（世卫组织），由于人口老龄化，这一数字将在未来几十年急剧增加。仅在英国，六分之一的人（估计有1100万到1200万）目前至少受到轻度听力损失的影响。可以说，听力损失最具破坏性的后果是难以理解言语，这影响了受影响个体的沟通、心理健康和认知过程。听力损失的最大原因是与年龄相关的变化，这几乎会影响到每个人的生活。虽然有些人很早就需要助听器，但有些人却能很好地应对听力损失，这可能是通过代偿性皮层过程实现的。在这个项目中，我们将发现为什么有些听力损失的人比其他人更能理解语言，即使他们可能有相似的听力能力。我们将全面模拟不同程度听力损失的言语理解脑节律。脑节律是大脑活动的节律模式，在所有行为、知觉和认知过程中都有作用。个体脑节律剖面将在静息状态脑电图（EEG）记录中使用我们先前开发的频谱指纹方法进行测量。言语理解将在现实生活中可能遇到的三种听力情况下进行测量，这些情况已被证明会受到听力损失的影响（嘈杂、快速和中断的言语）。听力水平将使用最先进、最高效的机器学习程序进行测量。这将在人口的大样本中进行，涵盖所有年龄和背景。综合电生理分析和详细的心理生理测试的创新结合将导致迄今为止最全面的关于内在大脑节律在不同程度听力损失的典型人群中言语感知中的作用的图片。此外，我们将测试是否有可能通过非侵入性地增强经颅磁刺激（TMS）的脑节律来改善自然语音感知。这种方法将有可能延迟甚至避免使用助听器的个人开始与年龄相关的听力损失，并改善社会和健康结果。

There are currently 430 million people worldwide with debilitating hearing loss (WHO) and this number will increase dramatically over the next decades due to the ageing population. In the UK alone, one in six individuals (an estimated 11 to 12 million) is currently affected by at least a mild hearing loss. Arguably the most devastating consequence of hearing loss is the difficulty to understand speech, which impacts communication, mental health, and cognitive processes in affected individuals. The single biggest cause of hearing loss are age-related changes, and this will affect nearly everyone to some extent in their life. While some individuals require hearing aids early on, others deal surprisingly well with hearing loss, likely through compensatory cortical processes. In this project, we will discover why some individuals with hearing loss can understand speech better than others, even though they might have similar hearing abilities. We will comprehensively model brain rhythms involved in speech comprehension with different levels of hearing loss. Brain rhythms are rhythmic patterns of brain activation that have a role in all behavioural, perceptual, and cognitive processes. Individual brain rhythm profiles will be measured in resting-state electroencephalography (EEG) recordings using our previously developed spectral fingerprinting approach. Speech comprehension will be measured in three listening situations that can be encountered in real life, and that have been shown to be affected by hearing loss (noisy, rapid, and interrupted speech). Hearing levels will be measured using state-of-the-art, efficient machine learning procedures. This will be done in a large sample of the population, spanning all ages and backgrounds. The innovative combination of comprehensive electrophysiological analyses and detailed psycho-physical testing will lead to the most comprehensive picture to date about the role of intrinsic brain rhythms in speech perception in the typical population with varying levels of hearing loss. Moreover, we will test whether it is possible to improve natural speech perception by non-invasively enhancing brain rhythms with transcranial magnetic stimulation (TMS). This approach will have the potential to delay or even avoid the use of hearing aids for individuals with beginning age-related hearing loss and improve social and health outcomes.