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基于多变量解码方法测量应激人群的ERP信号

Measurement of ERP Signals in Stressed Population Based on Multivariate Decoding Method
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摘要 多变量模式分类(解码)方法通常用于研究典型个体的神经认知神经加工,它们可用于量化单参与者神经信号中存在的信息。故本研究的目的是探究多变量解码方法是否可以比较应激人群与常人的神经表征。采用马斯特里赫特急性应激测试技术诱发应激,并在一项工作记忆任务中检查了应激人群和对照组的ERP,该任务涉及从显示的一侧记住2、4和(2加2分心)个项目并忽略另一侧。我们使用ERP的空间模式来解码显示的哪一侧被保存在工作记忆中。解码精度结果显示虽有较好的正确率但并无交互作用。最后对可能造成此结果的原因进行了探讨。 Multivariate pattern classification (decoding) methods are commonly used to study neurocogni-tive processing mechanisms in typical individuals, and they can be used to quantify the informa-tion present in neural signals of a single participant. Therefore, the purpose of this study was to investigate whether multivariate decoding methods can compare the neural representations of stressed and normal people. Stress was induced using the Maastricht Acute Stress Test technique, and the ERPs of the stressed and control groups were examined in a working memory task involving remembering 2, 4 and (2 plus 2 distractions) items and ignore the other side. We used the spatial pattern of the ERP to decode which side of the display was kept in working memory. Decoding accuracy results show that although there is a good accuracy rate, there is no interaction. Finally, the possible reasons for this result are discussed.
作者 刘旻 胡莎
出处 《心理学进展》 2022年第8期2706-2716,共11页 Advances in Psychology
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