Reward breaks through center‐surround inhibition via anterior insula. Issue 12 (29th September 2015)

• Record Type: Journal Article
• Authors: Wang, Lihui; Yu, Hongbo; Hu, Jie; Theeuwes, Jan; Gong, Xiaoliang; Xiang, Yang; Jiang, Changjun; Zhou, Xiaolin
• Is Part Of: Human brain mapping. Volume 36:Issue 12(2015:Dec.)
• Page Start: 5233
• Page End: 5251
• Publication Date: 2015-09-29
• Subjects: reward -- stimulus‐driven attention -- reward‐based attention -- anterior insula -- fMRI -- resting‐state fMRI -- dynamic causal modeling; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.23004
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: 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. Hum Brain Mapp 36:5233–5251, 2015 . © 2015 Wiley Periodicals, Inc.