The Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois 60208, USA.
J Neurosci. 2011 Jun 15;31(24):8780-5. doi: 10.1523/JNEUROSCI.0999-11.2011.
According to the dual stream model of auditory language processing, the dorsal stream is responsible for mapping sound to articulation and the ventral stream plays the role of mapping sound to meaning. Most researchers agree that the arcuate fasciculus (AF) is the neuroanatomical correlate of the dorsal steam; however, less is known about what constitutes the ventral one. Nevertheless, two hypotheses exist: one suggests that the segment of the AF that terminates in middle temporal gyrus corresponds to the ventral stream, and the other suggests that it is the extreme capsule that underlies this sound-to-meaning pathway. The goal of this study was to evaluate these two competing hypotheses. We trained participants with a sound-to-word learning paradigm in which they learned to use a foreign phonetic contrast for signaling word meaning. Using diffusion tensor imaging, a brain-imaging tool to investigate white matter connectivity in humans, we found that fractional anisotropy in the left parietal-temporal region positively correlated with the performance in sound-to-word learning. In addition, fiber tracking revealed a ventral pathway, composed of the extreme capsule and the inferior longitudinal fasciculus, that mediated auditory comprehension. Our findings provide converging evidence supporting the importance of the ventral steam, an extreme capsule system, in the frontal-temporal language network. Implications for current models of speech processing are also discussed.
根据听觉语言处理的双通路模型,背侧流负责将声音映射到发音,腹侧流则负责将声音映射到意义。大多数研究人员都认为弓状束(AF)是背侧流的神经解剖学相关物;然而,对于腹侧流的构成知之甚少。尽管如此,仍然存在两种假设:一种假设认为,在中颞叶终止的 AF 段对应于腹侧流,另一种假设则认为,是极囊构成了这条从声音到意义的通路。本研究的目的是评估这两种相互竞争的假设。我们采用了一种声音到单词学习的范式来训练参与者,让他们学习使用一种外来的语音对比来表示单词的意义。使用弥散张量成像(一种用于研究人类白质连接的脑成像工具),我们发现左顶颞区的各向异性分数与声音到单词学习的表现呈正相关。此外,纤维追踪显示了一条由极囊和下纵束组成的腹侧通路,该通路介导了听觉理解。我们的发现为腹侧流(一个极囊系统)在额颞语言网络中的重要性提供了一致的证据。还讨论了这些发现对当前语音处理模型的意义。