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抑郁和精神分裂症中的预期价值和预测误差异常。

Expected value and prediction error abnormalities in depression and schizophrenia.

机构信息

Centre for Neuroscience, Department of Psychiatry, University of Dundee, Mail Box 5, Level 5, Ninewells Hospital and Medical School, Dundee DD1 9SY, UK.

出版信息

Brain. 2011 Jun;134(Pt 6):1751-64. doi: 10.1093/brain/awr059. Epub 2011 Apr 10.

Abstract

The dopamine system has been linked to anhedonia in depression and both the positive and negative symptoms of schizophrenia, but it remains unclear how dopamine dysfunction could mechanistically relate to observed symptoms. There is considerable evidence that phasic dopamine signals encode prediction error (differences between expected and actual outcomes), with reinforcement learning theories being based on prediction error-mediated learning of associations. It has been hypothesized that abnormal encoding of neural prediction error signals could underlie anhedonia in depression and negative symptoms in schizophrenia by disrupting learning and blunting the salience of rewarding events, and contribute to psychotic symptoms by promoting aberrant perceptions and the formation of delusions. To test this, we used model based functional magnetic resonance imaging and an instrumental reward-learning task to investigate the neural correlates of prediction errors and expected-reward values in patients with depression (n=15), patients with schizophrenia (n=14) and healthy controls (n=17). Both patient groups exhibited abnormalities in neural prediction errors, but the spatial pattern of abnormality differed, with the degree of abnormality correlating with syndrome severity. Specifically, reduced prediction errors in the striatum and midbrain were found in depression, with the extent of signal reduction in the bilateral caudate, nucleus accumbens and midbrain correlating with increased anhedonia severity. In schizophrenia, reduced prediction error signals were observed in the caudate, thalamus, insula and amygdala-hippocampal complex, with a trend for reduced prediction errors in the midbrain, and the degree of blunting in the encoding of prediction errors in the insula, amygdala-hippocampal complex and midbrain correlating with increased severity of psychotic symptoms. Schizophrenia was also associated with disruption in the encoding of expected-reward values in the bilateral amygdala-hippocampal complex and parahippocampal gyrus, with the degree of disruption correlating with psychotic symptom severity. Neural signal abnormalities did not correlate with negative symptom severity in schizophrenia. These findings support the suggestion that a disruption in the encoding of prediction error signals contributes to anhedonia symptoms in depression. In schizophrenia, the findings support the postulate of an abnormality in error-dependent updating of inferences and beliefs driving psychotic symptoms. Phasic dopamine abnormalities in depression and schizophrenia are suggested by our observation of prediction error abnormalities in dopamine-rich brain areas, given the evidence for dopamine encoding prediction errors. The findings are consistent with proposals that psychiatric syndromes reflect different disorders of neural valuation and incentive salience formation, which helps bridge the gap between biological and phenomenological levels of understanding.

摘要

多巴胺系统与抑郁症中的快感缺失以及精神分裂症的阳性和阴性症状有关,但尚不清楚多巴胺功能障碍如何在机制上与观察到的症状相关。有大量证据表明,相位多巴胺信号编码预测误差(预期结果与实际结果之间的差异),强化学习理论基于预测误差介导的关联学习。人们假设,抑郁中快感缺失和精神分裂症阴性症状的神经预测误差信号编码异常可能通过破坏学习和钝化奖励事件的显著性来起作用,并通过促进异常感知和妄想的形成来导致精神病症状。为了检验这一点,我们使用基于模型的功能磁共振成像和仪器奖励学习任务来研究抑郁症患者(n=15)、精神分裂症患者(n=14)和健康对照者(n=17)的预测误差和预期奖励值的神经相关性。两个患者组都表现出神经预测误差异常,但异常的空间模式不同,异常程度与综合征严重程度相关。具体来说,在抑郁症中发现纹状体和中脑的预测误差减少,双侧尾状核、伏隔核和中脑的信号减少程度与快感缺失严重程度增加相关。在精神分裂症中,观察到尾状核、丘脑、岛叶和杏仁核-海马复合体的预测误差信号减少,中脑的预测误差信号减少呈趋势,岛叶、杏仁核-海马复合体和中脑预测误差信号的编码减弱程度与精神病症状严重程度增加相关。精神分裂症还与双侧杏仁核-海马复合体和旁海马回的预期奖励值编码中断有关,中断程度与精神病症状严重程度相关。精神分裂症中神经信号异常与阴性症状严重程度无关。这些发现支持这样一种观点,即预测误差信号编码的中断导致抑郁症中的快感缺失症状。在精神分裂症中,这些发现支持了一种假设,即错误依赖推理和信念更新异常导致精神病症状。基于多巴胺编码预测误差的证据,我们观察到多巴胺丰富脑区的预测误差异常,这表明抑郁和精神分裂症中存在相位多巴胺异常。这些发现与这样的观点一致,即精神科综合征反映了不同的神经估值和激励显著性形成障碍,这有助于弥合生物和现象学理解水平之间的差距。

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