Abstract linguistic structure correlates with temporal activity during naturalistic comprehension.
Abstract linguistic structure correlates with temporal activity during naturalistic comprehension.
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DOI：
10.1016/j.bandl.2016.04.008
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发表时间：
2016-06
影响因子：
2.5
通讯作者：
Hale JT
中科院分区：
文献类型：
--
作者：
Brennan JR;Stabler EP;Van Wagenen SE;Luh WM;Hale JT
关于句子理解的神经语言学解释确定了一个相关脑区网络，但没有详细说明流经这些脑区的信息。我们研究句法信息。大脑活动是涉及对层级语法的计算，还是仅仅反映线性顺序，就像马尔可夫链那样呢？为了解决这个问题，我们对不同解析模型所隐含的认知状态进行量化。我们将这些状态的处理复杂性预测与来自涉及句子理解的脑区的功能性磁共振成像（fMRI）时间进程进行比较。我们发现层级语法能够独立预测来自左侧颞叶前部和后部的时间进程。马尔可夫模型在这些区域以及包括额下回在内的更广泛网络中具有预测性。这些结果表明，虽然线性效应在语言网络中广泛存在，但左侧颞叶的某些区域处理抽象的、层级性的句法表征。
Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations.