心理学
颞叶
海马体
海马结构
神经科学
促进
语音识别
计算机科学
癫痫
作者
Neus Ramos-Escobar,Manuel R. Mercier,Agnès Trébuchon-Fonséca,Antoni Rodríguez-Fornells,Clément François,Daniele Schön
出处
期刊:Cortex
[Elsevier]
日期:2022-05-01
卷期号:150: 1-11
被引量:5
标识
DOI:10.1016/j.cortex.2022.01.017
摘要
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 learning stream. We also analyzed the event-related potentials (ERPs) of the test to evaluate the role of both regions in the recognition of newly segmented words. Results show that while auditory regions highly respond to syllable frequency, the hippocampus responds mostly to word frequency. Moreover, ERPs collected in the hippocampus show clear sensitivity to the familiarity of the items. These findings provide direct evidence of the involvement of the hippocampus in the speech segmentation process and suggest a hierarchical organization of auditory information during speech processing.
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