Wang Lihui, Yu Hongbo, Hu Jie, Theeuwes Jan, Gong Xiaoliang, Xiang Yang, Jiang Changjun, Zhou Xiaolin
Center for Brain and Cognitive Sciences and Department of Psychology, Peking University, Beijing, China.
Department of Experimental and Applied Psychology, Vrije Universiteit, Amsterdam, 1081 BT, The Netherlands.
Hum Brain Mapp. 2015 Dec;36(12):5233-51. doi: 10.1002/hbm.23004. Epub 2015 Sep 29.
Focusing attention on a target creates a center-surround inhibition such that distractors located close to the target do not capture attention. Recent research showed that a distractor can break through this surround inhibition when associated with reward. However, the brain basis for this reward-based attention is unclear. In this fMRI study, we presented a distractor associated with high or low reward at different distances from the target. Behaviorally the low-reward distractor did not capture attention and thus did not cause interference, whereas the high-reward distractor captured attention only when located near the target. Neural activity in extrastriate cortex mirrored the behavioral pattern. A comparison between the high-reward and the low-reward distractors presented near the target (i.e., reward-based attention) and a comparison between the high-reward distractors located near and far from the target (i.e., spatial attention) revealed a common frontoparietal network, including inferior frontal gyrus and inferior parietal sulcus as well as the visual cortex. Reward-based attention specifically activated the anterior insula (AI). Dynamic causal modelling showed that reward modulated the connectivity from AI to the frontoparietal network but not the connectivity from the frontoparietal network to the visual cortex. Across participants, the reward-based attentional effect could be predicted both by the activity in AI and by the changes of spontaneous functional connectivity between AI and ventral striatum before and after reward association. These results suggest that AI encodes reward-based salience and projects it to the stimulus-driven attentional network, which enables the reward-associated distractor to break through the surround inhibition in the visual cortex.
将注意力集中在一个目标上会产生一种中心-外周抑制，这样位于目标附近的干扰物就不会吸引注意力。最近的研究表明，当干扰物与奖励相关联时，它可以突破这种外周抑制。然而，这种基于奖励的注意力的大脑基础尚不清楚。在这项功能磁共振成像（fMRI）研究中，我们在与目标不同距离处呈现与高奖励或低奖励相关联的干扰物。在行为上，低奖励干扰物不会吸引注意力，因此不会造成干扰，而高奖励干扰物只有在位于目标附近时才会吸引注意力。纹外皮层的神经活动反映了行为模式。对在目标附近呈现的高奖励和低奖励干扰物之间的比较（即基于奖励的注意力），以及对位于目标附近和远离目标的高奖励干扰物之间的比较（即空间注意力），揭示了一个共同的额顶叶网络，包括额下回和顶下沟以及视觉皮层。基于奖励的注意力特别激活了前脑岛（AI）。动态因果模型表明，奖励调节了从AI到额顶叶网络的连接，但没有调节从额顶叶网络到视觉皮层的连接。在所有参与者中，基于奖励的注意力效应既可以通过AI中的活动来预测，也可以通过奖励关联前后AI与腹侧纹状体之间自发功能连接的变化来预测。这些结果表明，AI编码基于奖励的显著性，并将其投射到刺激驱动的注意力网络，这使得与奖励相关联的干扰物能够突破视觉皮层中的外周抑制。
