Di Liberto Giovanni M, O'Sullivan James A, Lalor Edmund C
Trinity College Institute of Neuroscience, School of Engineering, and Trinity Centre for Bioengineering Trinity College Dublin, Dublin 2, Ireland.
Trinity College Institute of Neuroscience, School of Engineering, and Trinity Centre for Bioengineering Trinity College Dublin, Dublin 2, Ireland.
Curr Biol. 2015 Oct 5;25(19):2457-65. doi: 10.1016/j.cub.2015.08.030. Epub 2015 Sep 24.
The human ability to understand speech is underpinned by a hierarchical auditory system whose successive stages process increasingly complex attributes of the acoustic input. It has been suggested that to produce categorical speech perception, this system must elicit consistent neural responses to speech tokens (e.g., phonemes) despite variations in their acoustics. Here, using electroencephalography (EEG), we provide evidence for this categorical phoneme-level speech processing by showing that the relationship between continuous speech and neural activity is best described when that speech is represented using both low-level spectrotemporal information and categorical labeling of phonetic features. Furthermore, the mapping between phonemes and EEG becomes more discriminative for phonetic features at longer latencies, in line with what one might expect from a hierarchical system. Importantly, these effects are not seen for time-reversed speech. These findings may form the basis for future research on natural language processing in specific cohorts of interest and for broader insights into how brains transform acoustic input into meaning.
人类理解言语的能力由一个分层听觉系统支撑，该系统的连续阶段处理声学输入中日益复杂的属性。有人提出，为了产生范畴性言语感知，尽管语音标记（例如音素）的声学特征存在变化，该系统必须对其引发一致的神经反应。在此，我们使用脑电图（EEG），通过表明当使用低级频谱时间信息和语音特征的范畴性标记来表示连续语音时，连续语音与神经活动之间的关系得到最佳描述，从而为这种范畴性音素级言语处理提供了证据。此外，音素与脑电图之间的映射在较长潜伏期时对语音特征的区分度更高，这与分层系统的预期相符。重要的是，对于时间反转的语音，这些效应并未出现。这些发现可能为未来针对特定感兴趣群体的自然语言处理研究以及更深入了解大脑如何将声学输入转化为意义奠定基础。
