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首页> 外文期刊>Neuropsychologia >Recognition memory advantage for negative emotional words has an early expiry date: Evidence from brain oscillations and ERPs
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Recognition memory advantage for negative emotional words has an early expiry date: Evidence from brain oscillations and ERPs

机译：负面情绪词语的识别记忆优势具有早期到期日：来自脑振荡和ERP的证据

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摘要

Evidence from prior studies has shown an advantage in recognition memory for emotional compared to neutral words. Whether this advantage is short-lived or rather extends over longer periods, as well as whether the effect depends on words’ valence (i.e., positive or negative), remains unknown. In the present ERP/EEG study, we investigated this issue by manipulating the lag distance (LAG-2, LAG-8 and LAG-16) between the presentation of old and new words in an online recognition memory task. LAG differences were observed at behavior, ERPs and in the theta frequency band. In line with previous studies, negative words were associated with faster reaction times, higher hit rates and increased amplitude in a positive ERP component between 386 and 564?ms compared to positive and neutral words. Remarkably, the interaction of LAG by EMOTION revealed that negative words were associated with better performance and larger ERPs amplitudes only at LAG-2. Also in the LAG-2 condition, emotional words (i.e., positive and negative words) induced a stronger desynchronization in the beta band between 386 and 542?ms compared to neutral words. These early enhanced memory effects for emotional words are discussed in terms of the Negative Emotional Valence Enhances Recapitulation (NEVER) model and the mobilization-minimization hypothesis.
机译：来自事先研究的证据表明，与中性单词相比，识别记忆的优势。这种优点是短暂的还是相当延伸超过更长的时间，以及效果是否取决于单词的价（即，正面或负面），仍然未知。在目前的ERP / EEG研究中，我们通过在在线识别记忆任务中的旧词的呈现与新单词的演示之间操纵滞后距离（LAG-2，LAG-8和LAG-16）来调查此问题。在行为，ERP和θ频带中观察到滞后差异。根据先前的研究，负词与更快的反应时间相关，较高的击球率和在386和564之间的正ERP组件中的振幅增加到386到564Ω·ms，与正和中立单词相比。值得注意的是，延迟的情绪的相互作用揭示了负面词语与LAG-2只有更好的性能和较大的ERPS幅度相关联。同样在LAG-2条件下，情绪词语（即正面和否定词）在386和542之间的β波段中引起更强的去同步，与中立单词相比。这些早期增强的情绪词语的记忆效果在负面情绪化的方面讨论了增强速度（从不）模型和动员 - 最小化假设。

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