Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression.
Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression.
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DOI：
10.1001/jamapsychiatry.2017.1713
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发表时间：
2017-08-01
期刊：
影响因子：
25.8
通讯作者：
Dolan RJ
中科院分区：
文献类型：
--
作者：
Rutledge RB;Moutoussis M;Smittenaar P;Zeidman P;Taylor T;Hrynkiewicz L;Lam J;Skandali N;Siegel JZ;Ousdal OT;Prabhu G;Dayan P;Fonagy P;Dolan RJ
重性抑郁症患者奖励预测错误对神经和情感的影响减弱了吗？在一项神经影像学研究中，抑郁症与非学习环境中奖励预测错误对神经影响的减少无关。在一项实验室行为研究和一项有1833名参与者的智能手机研究中，抑郁症也与奖励预测错误的情绪影响减少无关。在中度抑郁症中，与多巴胺相关的奖励预测错误的影响，在学习环境中被削弱，在非学习任务中是完整的。重度抑郁症（MDD）与表现奖励预测错误（RPE）的缺陷有关，这是经验和预测奖励之间的差异。奖励预测错误是强化学习模型中学习值的基础，由阶段性多巴胺释放表示，并且已知会影响瞬时情绪。 结合联合收割机功能性神经成像、计算建模和基于智能手机的大规模数据收集，在没有学习相关问题的情况下，测试抑郁减弱RPE影响的假设。收集了32名中度MDD患者和20名执行概率奖励任务的对照参与者的功能磁共振成像（fMRI）数据。一项风险决策任务，以重复的幸福评级作为衡量瞬间情绪的标准，也在实验室中对74名参与者进行了测试，并在1833名参与者中使用基于智能手机的平台进行了测试。本研究于2012年11月20日至2015年2月17日进行。在腹侧纹状体中测量血氧水平依赖性活动，腹侧纹状体是已知代表RPE的多巴胺靶区。在风险决策过程中测量瞬间情绪。在52名fMRI参与者（平均[SD]年龄，34.0 [9.1]岁）中，30名（58%）为女性，32名患有MDD。在实验室风险决策任务的74名参与者中（平均年龄34.2 [10.3]岁），44名（59%）为女性，54名患有MDD。在智能手机组中，543人（30%）有抑郁症史，1290人（70%）没有抑郁症史; 918人（50%）为女性，593人（32%）年龄小于30岁。与先前在强化学习任务中的结果相反，中度抑郁的个体在腹侧纹状体中显示出完整的RPE信号（z = 3.16; P = .002），与对照组（z = 0.91; P = .36）没有显著差异。在实验室（ρ =-0.54; P < 1 × 10−6）和智能手机（ρ =-0.30; P < 1 × 10−39）数据中，症状严重程度与基线情绪参数相关。然而，抑郁症参与者在瞬间情绪动力学的计算模型中显示出RPE和幸福感之间的完整关联（z = 4.55; P <0.001），与对照组相比（z =-0.42; P = 0.67）没有减弱。 RPE的神经和情感影响在重度抑郁症中是完整的。这些结果表明，抑郁症并不影响多巴胺能RPE的表达和衰减的RPE在以前的报告可能反映下游的影响更密切相关的异常行为。症状严重程度和基线情绪参数之间的相关性支持抑郁症和认知任务期间的瞬时情绪波动之间的关联。这些结果证明了智能手机在大规模计算表型中的潜力，这是计算精神病学的目标。这项队列研究使用功能性神经成像、计算建模和基于智能手机的数据评估了重度抑郁症患者与非抑郁症患者的奖励预测错误。
Is the neural and emotional impact of reward prediction errors attenuated in major depression? In a neuroimaging study, depression was not associated with a reduced neural impact of reward prediction errors in a nonlearning context. Depression also was not associated with a reduced emotional impact of reward prediction errors in a laboratory behavioral study and in a smartphone study with 1833 participants. In moderate major depression, impacts of reward prediction errors that are linked to dopamine, known to be attenuated in a learning context, are intact in nonlearning tasks. Major depressive disorder (MDD) is associated with deficits in representing reward prediction errors (RPEs), which are the difference between experienced and predicted reward. Reward prediction errors underlie learning of values in reinforcement learning models, are represented by phasic dopamine release, and are known to affect momentary mood. To combine functional neuroimaging, computational modeling, and smartphone-based large-scale data collection to test, in the absence of learning-related concerns, the hypothesis that depression attenuates the impact of RPEs. Functional magnetic resonance imaging (fMRI) data were collected on 32 individuals with moderate MDD and 20 control participants who performed a probabilistic reward task. A risky decision task with repeated happiness ratings as a measure of momentary mood was also tested in the laboratory in 74 participants and with a smartphone-based platform in 1833 participants. The study was conducted from November 20, 2012, to February 17, 2015. Blood oxygen level–dependent activity was measured in ventral striatum, a dopamine target area known to represent RPEs. Momentary mood was measured during risky decision making. Of the 52 fMRI participants (mean [SD] age, 34.0 [9.1] years), 30 (58%) were women and 32 had MDD. Of the 74 participants in the laboratory risky decision task (mean age, 34.2 [10.3] years), 44 (59%) were women and 54 had MDD. Of the smartphone group, 543 (30%) had a depression history and 1290 (70%) had no depression history; 918 (50%) were women, and 593 (32%) were younger than 30 years. Contrary to previous results in reinforcement learning tasks, individuals with moderate depression showed intact RPE signals in ventral striatum (z = 3.16; P = .002) that did not differ significantly from controls (z = 0.91; P = .36). Symptom severity correlated with baseline mood parameters in laboratory (ρ = −0.54; P < 1 × 10−6) and smartphone (ρ = −0.30; P < 1 × 10−39) data. However, participants with depression showed an intact association between RPEs and happiness in a computational model of momentary mood dynamics (z = 4.55; P < .001) that was not attenuated compared with controls (z = −0.42; P = .67). The neural and emotional impact of RPEs is intact in major depression. These results suggest that depression does not affect the expression of dopaminergic RPEs and that attenuated RPEs in previous reports may reflect downstream effects more closely related to aberrant behavior. The correlation between symptom severity and baseline mood parameters supports an association between depression and momentary mood fluctuations during cognitive tasks. These results demonstrate a potential for smartphones in large-scale computational phenotyping, which is a goal for computational psychiatry. This cohort study evaluates reward prediction errors in patients with major depressive disorder vs those without depression using functional neuroimaging, computational modeling, and smartphone-based data.
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影响因子：
168.9
作者：
Kupfer, David J.;Frank, Ellen;Phillips, Mary L.
通讯作者：
Phillips, Mary L.
DOI：
10.1176/appi.ajp.2008.08081201
发表时间：
2009-06
期刊：
The American journal of psychiatry
影响因子：
--
作者：
Pizzagalli DA;Holmes AJ;Dillon DG;Goetz EL;Birk JL;Bogdan R;Dougherty DD;Iosifescu DV;Rauch SL;Fava M
通讯作者：
Fava M
影响因子：
25
作者：
Huys QJ;Maia TV;Frank MJ
通讯作者：
Frank MJ
DOI：
10.1016/j.cub.2016.05.017
发表时间：
2016-06-20
期刊：
Current biology : CB
影响因子：
--
作者：
Rutledge RB;Smittenaar P;Zeidman P;Brown HR;Adams RA;Lindenberger U;Dayan P;Dolan RJ
通讯作者：
Dolan RJ
DOI：
10.1073/pnas.1014269108
发表时间：
2011-09-13
影响因子：
11.1
作者：
Glimcher, Paul W.
通讯作者：
Glimcher, Paul W.