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Neuroimage. 2019 Sep 16;203:116200. doi: 10.1016/j.neuroimage.2019.116200. [Epub ahead of print]

Uncovering cortical activations of discourse comprehension and their overlaps with common large-scale neural networks.

Author information

1
Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
2
Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: zuoxn@psych.ac.cn.
3
Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: yangyf@psych.ac.cn.

Abstract

We conducted a meta-analysis of 78 task-based functional magnetic resonance imaging (fMRI) studies (1976 total participants) to reveal underlying brain activations and their overlap with large-scale neural networks in the brain during general discourse comprehension and its sub-processes. We found that discourse comprehension involved a neural system consisting of widely distributed brain regions that comprised not only the bilateral perisylvian language zones, but also regions in the superior and medial frontal cortex and the medial temporal lobe. Moreover, this neural system can be categorized into several sub-systems representing various sub-processes of discourse comprehension, with the left inferior frontal gyrus and middle temporal gyrus serving as core regions across all sub-processes. At a large-scale network level, we found that discourse comprehension relied most heavily on the default network, particularly on its dorsal medial subsystem. The pattern associated with large-scale network cooperation varied according to the respective sub-processes required. Our results reveal the functional dissociation within the discourse comprehension neural system and highlight the flexible involvements of large-scale networks.

KEYWORDS:

Activation likelihood estimation; Default network; Discourse comprehension; Inference; Pragmatic interpretation; Text integration

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