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Categorical Speech Processing in Brocas Area: An fMRI Study Using Multivariate Pattern-Based Analysis

机译:布罗卡地区的分类语音处理:基于多元模式分析的功能磁共振成像研究

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摘要

Although much effort has been directed toward understanding the neural basis of speech processing, the neural processes involved in the categorical perception of speech have been relatively less studied, and many questions remain open. In this functional magnetic resonance imaging (fMRI) study, we probed the cortical regions mediating categorical speech perception using an advanced brain-mapping technique, whole-brain multivariate pattern-based analysis (MVPA). Normal healthy human subjects (native English speakers) were scanned while they listened to 10 consonant–vowel syllables along the /ba/–/da/ continuum. Outside of the scanner, individuals' own category boundaries were measured to divide the fMRI data into /ba/ and /da/ conditions per subject. The whole-brain MVPA revealed that Broca's area and the left pre-supplementary motor area evoked distinct neural activity patterns between the two perceptual categories (/ba/ vs /da/). Broca's area was also found when the same analysis was applied to another dataset (), which previously yielded the supramarginal gyrus using a univariate adaptation–fMRI paradigm. The consistent MVPA findings from two independent datasets strongly indicate that Broca's area participates in categorical speech perception, with a possible role of translating speech signals into articulatory codes. The difference in results between univariate and multivariate pattern-based analyses of the same data suggest that processes in different cortical areas along the dorsal speech perception stream are distributed on different spatial scales.
机译:尽管人们已经为理解语音处理的神经基础付出了很多努力,但是对语音的分类感知所涉及的神经过程的研究相对较少,并且许多问题仍然悬而未决。在这项功能性磁共振成像(fMRI)研究中,我们使用先进的脑图技术,基于全脑多元模式分析(MVPA)来探究介导分类语音感知的皮质区域。正常健康的人类受试者(说英语的母语人士)在/ ba / – / da /连续谱中听10个辅音元音节时进行了扫描。在扫描仪之外,对个人自己的类别边界进行了测量,以将fMRI数据分为每个受试者的/ ba /和/ da /条件。全脑MVPA揭示了Broca区域和左辅助运动区在两个知觉类别(/ ba / vs / da /)之间引起了明显的神经活动模式。当将相同的分析应用于另一个数据集()时,也发现了Broca区域。以前,该数据集使用单变量自适应-fMRI范例产生了上颌上回。来自两个独立数据集的一致MVPA结果强烈表明Broca的区域参与了分类语音感知,并可能将语音信号转换为发音代码。基于单变量和多变量模式的同一数据分析结果之间的差异表明,沿背侧语音感知流的不同皮质区域中的过程分布在不同的空间尺度上。

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