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序列决策中的行为偏好及其与焦虑的关系。

Behavioral preference in sequential decision-making and its association with anxiety.

机构信息

Department of Psychology, College of Psychology and Sociology, Shenzhen University, Shenzhen, China.

Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China.

出版信息

Hum Brain Mapp. 2018 Jun;39(6):2482-2499. doi: 10.1002/hbm.24016. Epub 2018 Feb 21.

Abstract

In daily life, people often make consecutive decisions before the ultimate goal is reached (i.e., sequential decision-making). However, this kind of decision-making has been largely overlooked in the literature. The current study investigated whether behavioral preference would change during sequential decisions, and the neural processes underlying the potential changes. For this purpose, we revised the classic balloon analogue risk task and recorded the electroencephalograph (EEG) signals associated with each step of decision-making. Independent component analysis performed on EEG data revealed that four EEG components elicited by periodic feedback in the current step predicted participants' decisions (gamble vs. no gamble) in the next step. In order of time sequence, these components were: bilateral occipital alpha rhythm, bilateral frontal theta rhythm, middle frontal theta rhythm, and bilateral sensorimotor mu rhythm. According to the information flows between these EEG oscillations, we proposed a brain model that describes the temporal dynamics of sequential decision-making. Finally, we found that the tendency to gamble (as well as the power intensity of bilateral frontal theta rhythms) was sensitive to the individual level of trait anxiety in certain steps, which may help understand the role of emotion in decision-making.

摘要

在日常生活中,人们经常在未达到最终目标之前做出连续的决策(即序贯决策)。然而,这种决策在文献中很大程度上被忽视了。本研究旨在探讨在序贯决策过程中行为偏好是否会发生变化,以及潜在变化的神经过程。为此,我们修改了经典的气球模拟风险任务,并记录了与决策过程中每个步骤相关的脑电图(EEG)信号。对 EEG 数据进行的独立成分分析表明,当前步骤中周期性反馈引发的四个 EEG 成分可以预测参与者在下一个步骤中的决策(赌博与不赌博)。按照时间顺序,这些成分依次为:双侧枕部α节律、双侧额部θ节律、中额部θ节律和双侧感觉运动μ节律。根据这些脑电振荡之间的信息流,我们提出了一个描述序贯决策的时动态的脑模型。最后,我们发现,在某些步骤中,赌博的倾向(以及双侧额部θ节律的功率强度)对特质焦虑的个体水平敏感,这可能有助于理解情绪在决策中的作用。

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