Data_Sheet_1_Neural Connectivity Underlying Reward and Emotion-Related Processing: Evidence From a Large-Scale Network Analysis.PDF

Neuroimaging techniques have advanced our knowledge about neurobiological mechanisms of reward and emotion processing. It remains unclear whether reward and emotion-related processing share the same neural connection topology and how intrinsic brain functional connectivity organization changes to support emotion- and reward-related prioritized effects in decision-making. The present study addressed these challenges using a large-scale neural network analysis approach. We applied this approach to two independent functional magnetic resonance imaging datasets, where participants performed a reward value or emotion associative matching task with tight control over experimental conditions. The results revealed that interaction between the Default Mode Network, Frontoparietal, Dorsal Attention, and Salience networks engaged distinct topological structures to support the effects of reward, positive and negative emotion processing. Detailed insights into the properties of these connections are important for understanding in detail how the brain responds in the presence of emotion and reward related stimuli. We discuss the linking of reward- and emotion-related processing to emotional regulation, an important aspect of regulation of human behavior in relation to mental health.

神经影像技术极大地推进了我们对奖励与情绪处理神经生物学机制的认知。然而，关于奖励与情绪相关处理是否共享相同的神经网络拓扑结构，以及大脑功能连通性组织如何适应以支持决策过程中情绪与奖励相关的优先效应，仍存在诸多未解之谜。本研究采用大规模神经网络分析方法，针对这些挑战展开了探讨。我们应用此方法对两个独立的脑磁共振成像数据集进行了分析，参与者在实验条件下执行了奖励价值或情绪关联匹配任务。研究结果揭示了默认模式网络、额顶叶网络、背侧注意力网络和显著性网络之间的交互作用，它们通过独特的拓扑结构支持了奖励、积极和消极情绪处理的效果。深入了解这些连接的性质，对于细致理解大脑在情绪与奖励相关刺激出现时的反应至关重要。我们进一步讨论了奖励与情绪相关处理与情绪调节之间的联系，这是与心理健康密切相关的人类行为调节的重要方面。