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首页> 外文期刊>Neuroscience and Biobehavioral Reviews >Common and distinct networks underlying reward valence and processing stages: a meta-analysis of functional neuroimaging studies.
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Common and distinct networks underlying reward valence and processing stages: a meta-analysis of functional neuroimaging studies.

机译:奖励价和加工阶段所依据的常见且不同的网络:功能神经影像研究的荟萃分析。

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摘要

To better understand the reward circuitry in human brain, we conducted activation likelihood estimation (ALE) and parametric voxel-based meta-analyses (PVM) on 142 neuroimaging studies that examined brain activation in reward-related tasks in healthy adults. We observed several core brain areas that participated in reward-related decision making, including the nucleus accumbens (NAcc), caudate, putamen, thalamus, orbitofrontal cortex (OFC), bilateral anterior insula, anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC), as well as cognitive control regions in the inferior parietal lobule and prefrontal cortex (PFC). The NAcc was commonly activated by both positive and negative rewards across various stages of reward processing (e.g., anticipation, outcome, and evaluation). In addition, the medial OFC and PCC preferentially responded to positive rewards, whereas the ACC, bilateral anterior insula, and lateral PFC selectively responded to negative rewards. Reward anticipation activated the ACC, bilateral anterior insula, and brain stem, whereas reward outcome more significantly activated the NAcc, medial OFC, and amygdala. Neurobiological theories of reward-related decision making should therefore take distributed and interrelated representations of reward valuation and valence assessment into account.
机译:为了更好地了解人脑中的奖励电路,我们对142项神经成像研究进行了激活可能性估计(ALE)和基于参数体素的荟萃分析(PVM),这些研究检查了健康成年人奖励相关任务中的大脑激活。我们观察到了参与奖励相关决策的几个核心大脑区域,包括伏伏核(NAcc),尾状,壳壳,丘脑,眶额皮质(OFC),双侧前岛鞘,前扣带回皮质(ACC)和后扣带回皮质( PCC)以及顶下小叶和前额叶皮层(PFC)中的认知控制区域。 NAcc通常在奖励处理的各个阶段(例如,预期,结果和评估)被正面和负面奖励所激活。此外,内侧OFC和PCC优先对正向奖赏做出反应,而ACC,双侧前岛绝缘和外侧PFC对负向奖赏有选择地做出响应。奖励预期激活了ACC,双侧前岛和脑干,而奖励结果更显着地激活了NAcc,内侧OFC和杏仁核。因此,与奖励有关的决策的神经生物学理论应考虑奖励评估和​​效价评估的分布式和相互关联的表示形式。

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