The prediction-error hypothesis of schizophrenia: new data point to circuit-specific changes in dopamine activity.
The prediction-error hypothesis of schizophrenia: new data point to circuit-specific changes in dopamine activity.
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DOI：
10.1038/s41386-021-01188-y
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发表时间：
2022-03
期刊：
影响因子：
--
通讯作者：
Sharpe MJ
中科院分区：
文献类型：
--
作者：
Millard SJ;Bearden CE;Karlsgodt KH;Sharpe MJ
精神分裂症是一种严重的精神疾病，影响着全世界 2100 万人。精神分裂症患者会出现精神病、妄想、冷漠、快感缺乏和认知缺陷等症状。引人注目的是，精神分裂症的特点是学习悖论，涉及从奖励事件中学习的困难，同时“过度学习”不相关或中性的信息。虽然多巴胺能信号传导功能障碍长期以来与精神分裂症的病理生理学有关，但解释这种学习悖论的内聚框架仍然难以捉摸。最近，大量新研究调查了多巴胺如何促进强化学习，这表明中脑多巴胺以复杂的方式促进强化学习，这是以前没有想到的。这一新数据为多巴胺信号传导如何影响精神分裂症的症状带来了新的可能性。基于最近的工作，我们提出了一个新的神经框架，用于我们如何在强化学习模型的背景下设想特定的多巴胺回路导致精神分裂症的这种学习悖论。此外，我们讨论了使用尖端神经科学技术进行临床前研究的途径，可以测试该模型的各个方面。最终，希望这篇综述能够促进更多的研究在精神分裂症的临床前模型中利用特定的强化学习范例，以协调看似不同的症状学并开发更有效的治疗方法。
Schizophrenia is a severe psychiatric disorder affecting 21 million people worldwide. People with schizophrenia suffer from symptoms including psychosis and delusions, apathy, anhedonia, and cognitive deficits. Strikingly, schizophrenia is characterised by a learning paradox involving difficulties learning from rewarding events, whilst simultaneously ‘overlearning’ about irrelevant or neutral information. While dysfunction in dopaminergic signalling has long been linked to the pathophysiology of schizophrenia, a cohesive framework that accounts for this learning paradox remains elusive. Recently, there has been an explosion of new research investigating how dopamine contributes to reinforcement learning, which illustrates that midbrain dopamine contributes in complex ways to reinforcement learning, not previously envisioned. This new data brings new possibilities for how dopamine signalling contributes to the symptomatology of schizophrenia. Building on recent work, we present a new neural framework for how we might envision specific dopamine circuits contributing to this learning paradox in schizophrenia in the context of models of reinforcement learning. Further, we discuss avenues of preclinical research with the use of cutting-edge neuroscience techniques where aspects of this model may be tested. Ultimately, it is hoped that this review will spur to action more research utilising specific reinforcement learning paradigms in preclinical models of schizophrenia, to reconcile seemingly disparate symptomatology and develop more efficient therapeutics.
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DOI：
10.1186/1755-7682-3-24
发表时间：
2010-10-06
期刊：
International archives of medicine
影响因子：
--
作者：
Arias-Carrión O;Stamelou M;Murillo-Rodríguez E;Menéndez-González M;Pöppel E
通讯作者：
Pöppel E
影响因子：
5.3
作者：
Adams, B;Moghaddam, B
通讯作者：
Moghaddam, B
影响因子：
10.6
作者：
Ceaser, Alan E.;Goldberg, Terry E.;Gold, James M.
通讯作者：
Gold, James M.
影响因子：
4.6
作者：
Barch DM;Carter CS;Gold JM;Johnson SL;Kring AM;MacDonald AW;Pizzagalli DA;Ragland JD;Silverstein SM;Strauss ME
通讯作者：
Strauss ME
影响因子：
4.7
作者：
Brisch R;Saniotis A;Wolf R;Bielau H;Bernstein HG;Steiner J;Bogerts B;Braun K;Jankowski Z;Kumaratilake J;Henneberg M;Gos T
通讯作者：
Gos T