Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, United Kingdom.
Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, United Kingdom.
Hear Res. 2024 Sep 15;451:109081. doi: 10.1016/j.heares.2024.109081. Epub 2024 Jul 11.
Speech-in-noise (SIN) perception is a fundamental ability that declines with aging, as does general cognition. We assess whether auditory cognitive ability, in particular short-term memory for sound features, contributes to both. We examined how auditory memory for fundamental sound features, the carrier frequency and amplitude modulation rate of modulated white noise, contributes to SIN perception. We assessed SIN in 153 healthy participants with varying degrees of hearing loss using measures that require single-digit perception (the Digits-in-Noise, DIN) and sentence perception (Speech-in-Babble, SIB). Independent variables were auditory memory and a range of other factors including the Pure Tone Audiogram (PTA), a measure of dichotic pitch-in-noise perception (Huggins pitch), and demographic variables including age and sex. Multiple linear regression models were compared using Bayesian Model Comparison. The best predictor model for DIN included PTA and Huggins pitch (r = 0.32, p < 0.001), whereas the model for SIB included the addition of auditory memory for sound features (r = 0.24, p < 0.001). Further analysis demonstrated that auditory memory also explained a significant portion of the variance (28 %) in scores for a screening cognitive test for dementia. Auditory memory for non-speech sounds may therefore provide an important predictor of both SIN and cognitive ability.
言语噪声辨别(SIN)感知能力随着年龄的增长而下降,一般认知能力也是如此。我们评估了听觉认知能力,特别是对声音特征的短期记忆,是否对这两者都有贡献。我们研究了对基本声音特征(调制白噪声的载波频率和调制度率)的听觉记忆如何有助于 SIN 感知。我们使用需要个位数感知的测试(噪声中的数字,DIN)和句子感知(嘈杂语音中的句子,SIB),对 153 名听力损失程度不同的健康参与者进行了 SIN 评估。自变量包括听觉记忆和一系列其他因素,包括纯音听阈(PTA)、双音噪声中音调感知的衡量指标(Huggins 音调)以及包括年龄和性别在内的人口统计学变量。使用贝叶斯模型比较比较了多个线性回归模型。DIN 的最佳预测模型包括 PTA 和 Huggins 音调(r = 0.32,p < 0.001),而 SIB 的模型则包括对声音特征的听觉记忆的加入(r = 0.24,p < 0.001)。进一步的分析表明,听觉记忆也解释了痴呆症筛查认知测试分数的很大一部分方差(28%)。因此,非言语声音的听觉记忆可能是 SIN 和认知能力的重要预测因素。