Humans can easily distinguish many sounds in the environment, but speech and music are uniquely important. Previous studies, mostly using fMRI, have identified separate regions of the brain that respond selectively for speech and music. Yet there is little evidence that brain responses are larger and more temporally precise for human-specific sounds like speech and music compared to other types of sounds, as has been found for responses to species-specific sounds in other animals. We recorded EEG as healthy, adult subjects listened to various types of two-second-long natural sounds. By classifying each sound based on the EEG response, we found that speech, music, and impact sounds were classified better than other natural sounds. But unlike impact sounds, the classification accuracy for speech and music dropped for synthesized sounds that have identical frequency and modulation statistics based on a subcortical model, indicating a selectivity for higher-order features in these sounds. Lastly, the patterns in average power and phase consistency of the two-second EEG responses to each sound replicated the patterns of speech and music selectivity observed with classification accuracy. Together with the classification results, this suggests that the brain produces temporally individualized responses to speech and music sounds that are stronger than the responses to other natural sounds. In addition to highlighting the importance of speech and music for the human brain, the techniques used here could be a cost-effective, temporally precise, and efficient way to study the human brain's selectivity for speech and music in other populations.

中文翻译：

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基于 EEG 的自然声音分类揭示了对语音和音乐的特殊反应

人类可以轻松区分环境中的许多声音，但语音和音乐尤为重要。以前的研究，主要是使用 fMRI，已经确定了大脑的不同区域，这些区域对语音和音乐有选择性的反应。然而，几乎没有证据表明，与其他类型的声音相比，大脑对人类特定声音（如语音和音乐）的反应更大且在时间上更精确，正如其他动物对物种特定声音的反应所发现的那样。我们将脑电图记录为健康的成年受试者聆听各种类型的 2 秒长的自然声音。通过根据 EEG 响应对每种声音进行分类，我们发现语音、音乐和撞击声的分类效果优于其他自然声音。但与撞击声不同的是 对于基于皮层下模型的具有相同频率和调制统计数据的合成声音，语音和音乐的分类准确度下降，表明对这些声音中的高阶特征具有选择性。最后，对每个声音的两秒 EEG 响应的平均功率和相位一致性模式复制了以分类精度观察到的语音和音乐选择性模式。与分类结果一起，这表明大脑对语音和音乐声音产生的时间个性化反应比对其他自然声音的反应更强。除了强调语音和音乐对人脑的重要性之外，这里使用的技术可能是一种经济高效、时间精确且有效的研究人脑的方法。