论文标题
海马和听觉对语音细分的贡献
Hippocampal and auditory contributions to speech segmentation
论文作者
论文摘要
已提出统计学习是一种结构和分割多种感觉方式的信息流的机制。先前的研究提出,内侧颞叶,尤其是海马,对于在视觉方式中解析流可能至关重要。但是,海马参与听觉统计学习,特别是在语音分割中的参与还不太清楚。为了探索基于统计学习的海马在语音分割中的作用,我们将七个耐药性颞叶癫痫患者暴露于连续的三基曲线伪造的流中,并记录了颅内立体观念型电脑造影(SEEG)。我们使用频率分析分析来量化海马和听觉区域的神经元同步,以与流的单词和音节的时间结构。结果表明,尽管听觉区域对音节频率有很高的反应,但海马主要对单词频率做出反应。这些发现提供了直接证据表明海马参与语音分割过程,并在语音处理过程中提出了一个听觉信息的等级组织。
Statistical learning has been proposed as a mechanism to structure and segment the continuous flow of information in several sensory modalities. Previous studies proposed that the medial temporal lobe, and in particular the hippocampus, may be crucial to parse the stream in the visual modality. However, the involvement of the hippocampus in auditory statistical learning, and specifically in speech segmentation is less clear. To explore the role of the hippocampus in speech segmentation based on statistical learning, we exposed seven pharmaco-resistant temporal lobe epilepsy patients to a continuous stream of trisyllabic pseudowords and recorded intracranial stereotaxic electro-encephalography (sEEG). We used frequency-tagging analysis to quantify neuronal synchronization of the hippocampus and auditory regions to the temporal structure of words and syllables of the stream. Results show that while auditory regions highly respond to syllable frequency, the hippocampus responds mostly to word frequency. These findings provide direct evidence of the involvement of the hippocampus in speech segmentation process and suggest a hierarchical organization of auditory information during speech processing.