Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, 15260, USA.
Sci Rep. 2023 Jun 23;13(1):10216. doi: 10.1038/s41598-023-37173-2.
Neurophysiological studies suggest that intrinsic brain oscillations influence sensory processing, especially of rhythmic stimuli like speech. Prior work suggests that brain rhythms may mediate perceptual grouping and selective attention to speech amidst competing sound, as well as more linguistic aspects of speech processing like predictive coding. However, we know of no prior studies that have directly tested, at the single-trial level, whether brain oscillations relate to speech-in-noise outcomes. Here, we combined electroencephalography while simultaneously measuring intelligibility of spoken sentences amidst two different interfering sounds: multi-talker babble or speech-shaped noise. We find that induced parieto-occipital alpha (7-15 Hz; thought to modulate attentional focus) and frontal beta (13-30 Hz; associated with maintenance of the current sensorimotor state and predictive coding) oscillations covary with trial-wise percent-correct scores; importantly, alpha and beta power provide significant independent contributions to predicting single-trial behavioral outcomes. These results can inform models of speech processing and guide noninvasive measures to index different neural processes that together support complex listening.
神经生理学研究表明，内在的脑振荡会影响感觉处理，特别是对像语音这样的节奏性刺激。先前的工作表明，脑节律可能介导语音在竞争声音中的知觉分组和选择性注意，以及语音处理的更语言学方面，如预测编码。然而，我们不知道以前有任何研究直接在单试次水平上测试脑振荡是否与语音在噪声中的结果有关。在这里，我们结合了脑电图，同时在两种不同的干扰声音中测量口语句子的可理解性：多说话者杂音或语音噪声。我们发现，诱导的顶枕部 alpha（7-15 Hz；被认为调节注意力焦点）和额叶 beta（13-30 Hz；与当前感觉运动状态的维持和预测编码有关）振荡与试验性百分比正确分数相关；重要的是，alpha 和 beta 功率对预测单试次行为结果有显著的独立贡献。这些结果可以为语音处理模型提供信息，并指导非侵入性措施来指示共同支持复杂听力的不同神经过程。
