[1]董小蕾,郭宗君,修红,等. 风险决策预期效用的神经行为模式研究[J].青岛大学学报(医学版),2018,54(03 ):321-324.[doi:10.11712/jms201803016]
 DONG Xiaolei,GUO Zongjun,XIU Hong,et al. NEURAL AND BEHAVIORAL MODELS OF EXPECTED VALUE IN DECISION-MAKING UNDER RISK[J].JOURNAL OF QINGDAO UNIVERSITY (MEDICAL SCIENCES),2018,54(03 ):321-324.[doi:10.11712/jms201803016]
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 风险决策预期效用的神经行为模式研究()
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《青岛大学学报(医学版)》[ISSN:2096-5532/CN:37-1217/R]

卷:
第54卷
期数:
2018年03 期
页码:
321-324
栏目:
出版日期:
2018-05-29

文章信息/Info

Title:
 NEURAL AND BEHAVIORAL MODELS OF EXPECTED VALUE IN DECISION-MAKING UNDER RISK
作者:
 董小蕾1郭宗君1修红2李蕾1刘世恩3马文帅3
 青岛大学附属医院,山东 青岛 266003 1 老年医学科; 2 护理部; 3 放射科
Author(s):
 DONG Xiaolei GUO Zongjun XIU Hong LI Lei LIU Shien MA Wenshuai
 Department of Geriatrics, The Affiliated Hospital of Qingdao University, Qingdao 266003, China
关键词:
 决策预期心理奖励惩罚
Keywords:
 decision making anticipation psychological reward punishment brain
分类号:
R749
DOI:
10.11712/jms201803016
文献标志码:
A
摘要:
 目的 观察风险决策预期效用(EV)加工时的行为模式与脑激活模式及其相关关系。
方法 选取26例正常人,在E-Prime系统下完成60%概率得到奖励的风险决策任务,同时记录选择模式、损益得分等。应用SA-9800脑功能视听觉刺激系统和GE 3.0 T超导型核磁共振扫描仪对受试者进行决策加工时的全脑同步扫描,SPM8及REST软件进行数据分析,xjview软件观察和分析脑激活情况。SPSS 17.0软件分析行为模式得分与脑激活强度的关系。
结果 风险偏好得分(12.75±2.85)分,保持策略得分(9.04±2.33)分,转换策略得分(2.96±2.33)分,总赢利得(49.50±11.57)分。EV时双侧前额叶(PFC)、右侧扣带回、双侧壳核、左侧脑岛、右侧颞叶、左侧顶上小叶、右侧顶下小叶、左侧枕中回、双侧小脑后叶被激活。相关分析显示,风险偏好与EV时激活的左眶额叶(OFC)(r=0.59,P<0.05)和左侧壳核(r=0.66,P<0.05)激活强度呈正相关,与左侧脑岛激活强度呈负相关(r=-0.65,P<0.05);保持策略与EV时左OFC激活呈正相关(r=0.57,P<0.05);总赢利得分与EV时左OFC(r=0.61,P<0.05)和左侧壳核(r=0.64,P<0.05)均激活强度呈正相关,与左侧脑岛激活强度呈负相关(r=-0.63,P<0.05)。
结论 决策预期效用是以壳核激活为代表的奖赏趋近行为脑功能区(保持策略)、以脑岛激活为代表的损失规避行为脑功能区和以前额叶激活为代表的奖损调枢行为脑功能区(转换策略)同时作用下的决策活动。
Abstract:
 Objective To observe the behavioral model, brain activation model, and relationship between these two models during expected value (EV) processing in decision-making under risk.
Methods Twenty-six healthy volunteers were enrolled as subjects. In the E-Prime system, the subjects received a task of decision-making under risk, which offered a 60% chance to win a reward. The decision-making model and profit and loss scores were recorded. The SA-9800 brain function audiovisual stimulation system and GE 3.0 T magnetic resonance scanner were used to scan the brains of the subjects when they were making decisions. The SPM8 and REST programs were used for data analyses. The xjview program was used to observe and evaluate brain activation. The SPSS 17.0 program was used to analyze the relationship between the behavioral model and brain activation intensity.
Results The scores for risk preference, keeping strategy, changing strategy, and total profit were 12.75±2.85, 9.04±2.33, 2.96±2.33, and 49.50±11.57, respectively. During EV processing, the activated brain regions contained bilateral prefrontal cortex (PFC), right cingulate gyrus, bilateral putamen, left insular, right temporal lobe, left superior parietal lobule, right inferior pa-
rietal lobule, left middle occipital gyrus, and bilateral posterior lobe of cerebellum. According to the correlation analyses, the score for risk preference was positively correlated with the activation intensity of left orbital frontal cortex (OFC) and left putamen (r=0.59,0.66;P<0.05), and negatively correlated with the activation intensity of left insular during EV processing (r=-0.65,P<0.05); the score for keeping strategy was positively correlated with the activation intensity of left OFC during EV processing (r=0.57,P<0.05); the score for total profit was positively correlated with the activation intensity of left OFC and left putamen (r=0.61,0.64;P<0.05), and negatively correlated with the activation intensity of left insular during EV processing (r=-0.63,P<0.05).
Conclusion EV in decision-making is an export of three brain functional regions: reward-approaching behavior represented by putamen activation (keeping strategy), loss-prevention behavior represented by insular activation, and reward-loss-adjusting behavior represented by PFC (changing strategy).
更新日期/Last Update: 2018-06-05