Jaeger Manuela, Zion Golumbic Elana, Bleichner Martin G
Neurophysiology of Everyday Life Group, Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.
Neurobiol Lang (Camb). 2025 Sep 5;6. doi: 10.1162/nol.a.14. eCollection 2025.
This study investigates how selective auditory attention influences the lexical speech segmentation process to phonemes and words in a two competing speaker scenario. Using electroencephalography recordings from 20 participants, we applied temporal response function analysis to distinguish attention-driven neural activity to phoneme and word onsets for the attended and ignored speech stream separately. Our results reveal distinct attention effects for phoneme and word onsets. Phoneme onsets elicited significant selective attention effects at an early (18-94 ms, P1), middle (186-252 ms, P2), and late (302-382 ms, N2) time window. In contrast, word onsets showed attention effects only at a middle (192-280 ms, P2) and late (348-386 ms, N2) time window, occurring slightly later than phoneme-related effects. Prediction accuracy analyses demonstrated stronger model performance for the attended speech stream across all models, with notable improvements in prediction accuracy from a word model to a phoneme model to a combined word and phoneme model. These findings are in accordance with both hierarchical and parallel processing frameworks, where selective attention enhances lexical segmentation for attended speech, improving prediction accuracy. Early attention effects observed for phoneme onsets underscore their role in low-level speech processing, while late attention effects for word onsets may reflect higher level processing. This study highlights the importance of selective attention in neural speech tracking and provides insights into auditory processing mechanisms underlying speech comprehension in complex acoustic environments.
本研究调查了在两个竞争说话者的场景中，选择性听觉注意力如何影响词汇语音分割为音素和单词的过程。我们使用了20名参与者的脑电图记录，应用时间响应函数分析来分别区分注意力驱动的神经活动对被关注和被忽略语音流中的音素和单词起始的反应。我们的结果揭示了音素和单词起始的不同注意力效应。音素起始在早期（18 - 94毫秒，P1）、中期（186 - 252毫秒，P2）和晚期（302 - 382毫秒，N2）时间窗口引发了显著的选择性注意力效应。相比之下，单词起始仅在中期（192 - 280毫秒，P2）和晚期（348 - 386毫秒，N2）时间窗口显示出注意力效应，比与音素相关的效应出现得稍晚。预测准确性分析表明，在所有模型中，被关注语音流的模型性能更强，从单词模型到音素模型再到单词和音素组合模型，预测准确性有显著提高。这些发现与分层和平行处理框架均相符，其中选择性注意力增强了对被关注语音的词汇分割，提高了预测准确性。对音素起始观察到的早期注意力效应强调了它们在低级语音处理中的作用，而对单词起始的晚期注意力效应可能反映了更高层次的处理。本研究强调了选择性注意力在神经语音跟踪中的重要性，并为复杂声学环境中语音理解的听觉处理机制提供了见解。
