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风险决策中与年龄相关的神经策略改变

The Age-related Neural Strategy Alterations in Decision Making Under Risk.

作者信息

Peng Xue-Rui, Lei Xu, Xu Peng, Yu Jing

机构信息

Faculty of Psychology, Southwest University, Chongqing 400715, China.

School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.

出版信息

Neuroscience. 2020 Aug 1;440:30-38. doi: 10.1016/j.neuroscience.2020.05.017. Epub 2020 May 21.

Abstract

Previous studies have shown that aging is associated with changes in decision behavior. However, the neural mechanisms that underpin such age differences are inadequately understood. In this study, we aim to characterize the optimal neural model underlying a dynamic decision making task in both young and older adults, and further examine the age differences from the perspective of effective connectivity. Twenty-five young and 23 older adults performed a dynamic risk taking task, i.e., the balloon analogue risk task, in the functional magnetic resonance imaging scanner. The dynamic causal modeling analysis, with the coupling between the ventromedial prefrontal cortex (VMPFC), dorsolateral prefrontal cortex (DLPFC) and anterior insula (AI) that were identified in our task-related activation and psychophysiological interaction analysis, was performed to address the best fitting neural model and characterize age differences. Although both age groups adopted the same optimal model with bidirectional connection between the VMPFC and DLPFC, older adults exhibited up-regulation in several connections and among which the increased modulatory effect of AI-to-VMPFC subserving their decision quality. Our finding suggests that older adults might utilize different neural strategy via compensation to counteract the impact of advanced age in risk taking process.

摘要

先前的研究表明,衰老与决策行为的变化有关。然而,支撑这种年龄差异的神经机制尚未得到充分理解。在本研究中,我们旨在刻画年轻人和老年人在动态决策任务中潜在的最优神经模型,并从有效连接性的角度进一步研究年龄差异。25名年轻人和23名老年人在功能磁共振成像扫描仪中执行了一项动态冒险任务,即气球模拟风险任务。进行动态因果模型分析,结合在我们的任务相关激活和心理生理交互分析中确定的腹内侧前额叶皮层(VMPFC)、背外侧前额叶皮层(DLPFC)和前脑岛(AI)之间的耦合,以确定最佳拟合神经模型并刻画年龄差异。尽管两个年龄组都采用了相同的最优模型,即VMPFC和DLPFC之间的双向连接,但老年人在几个连接中表现出上调,其中AI对VMPFC的调节作用增强有助于他们的决策质量。我们的发现表明,老年人可能通过补偿采用不同的神经策略来抵消高龄对冒险过程的影响。

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