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

目前全世界有4.3亿人患有衰弱性听力损失(WHO)，由于人口老龄化，这一数字在未来几十年将大幅增加。仅在英国，每六个人中就有一个人(估计为1100万至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理解语言的困难，这会影响受影响个人的沟通、心理健康和认知过程。导致听力损失的最大原因是与年龄相关的变化，这将在一定程度上影响几乎每个人的生活。虽然有些人在早期需要助听器，但另一些人处理听力损失的能力出奇地好，可能是通过代偿性皮质过程。在这个项目中，我们将发现为什么一些听力损失的人比其他人能更好地理解语言，即使他们的听力可能相似。我们将对不同程度听力损失的语音理解所涉及的大脑节律进行综合建模。大脑节律是大脑活动的节奏模式，在所有行为、知觉和认知过程中都有作用。我们将使用我们之前开发的光谱指纹方法，在静息状态脑电(EEG)记录中测量个人大脑节律曲线。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，这些情况已经被证明受到听力损失的影响(嘈杂、快速和中断的语音)。听力水平将使用最先进、高效的机器学习程序进行测量。这将在所有年龄和背景的人群中进行大样本调查。全面的电生理分析和详细的心理-物理测试的创新组合将带来迄今为止关于不同程度听力损失的典型人群中内在大脑节律在言语感知中的作用的最全面的图景。此外，我们将测试是否有可能通过经颅磁刺激(TMS)非侵入性地增强大脑节律来改善自然语音感知。这种方法将有可能推迟甚至避免对年龄相关性听力损失患者使用助听器，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.