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  1.  45
    Bilingual Processing Mechanisms of Scientific Metaphors and Conventional Metaphors: Evidence via a Contrastive Event-Related Potentials Study.Xuemei Tang, Lexian Shen, Peng Yang, Yanhong Huang, Shaojuan Huang, Min Huang & Wei Ren - 2022 - Frontiers in Psychology 13.
    To study the different mechanisms of understanding figurative language in a speaker’s native language and their second language, this study investigated how scientific metaphors in Chinese and English are electrophysiologically processed via event-related potential experimentation. Compared with the metaphors from daily life or in literary works, scientific metaphors tend to involve both a more complicated context structure and a distinct knowledge-inferencing process. During the N400 time window, English scientific metaphors elicited more negative N400s than Chinese ones at the parietal region. (...)
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    Hemispheric Processing of Chinese Scientific Metaphors: Evidence via Hemifield Presentation.Min Huang, Lexian Shen, Shuyuan Xu, Yanhong Huang, Shaojuan Huang & Xuemei Tang - 2022 - Frontiers in Psychology 13.
    The role of the two hemispheres in processing metaphoric language is controversial. In order to complement current debates, the current divided visual field study introduced scientific metaphors as novel metaphors, presenting orientation mapping from the specific and familiar domains to the abstract and unfamiliar domains, to examine hemispheric asymmetry in metaphoric processing. Twenty-four Chinese native speakers from science disciplines took part in the experiment. The participants were presented with four types of Chinese word pairs: scientific metaphors, conventional metaphors, literal word (...)
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    Emotional State and Feedback-Related Negativity Induced by Positive, Negative, and Combined Reinforcement.Shuyuan Xu, Yuyan Sun, Min Huang, Yanhong Huang, Jing Han, Xuemei Tang & Wei Ren - 2021 - Frontiers in Psychology 12:647263.
    Reinforcement learning relies on the reward prediction error (RPE) signals conveyed by the midbrain dopamine system. Previous studies showed that dopamine plays an important role in both positive and negative reinforcement. However, whether various reinforcement processes will induce distinct learning signals is still unclear. In a probabilistic learning task, we examined RPE signals in different reinforcement types using an electrophysiology index, namely, the feedback-related negativity (FRN). Ninety-four participants were randomly assigned into four groups: base (no money incentive), positive reinforcement (presentation (...)
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