Reward breaks through center-surround inhibition via anterior insula.

Authors:
Lihui Wang
Lihui Wang
Imperial College London
United Kingdom
Hongbo Yu
Hongbo Yu
Shanghai Jiao Tong University School of Medicine
China
Jie Hu
Jie Hu
Liver Cancer Institute
Fort Worth | United States
Jan Theeuwes
Jan Theeuwes
Vrije Universiteit
Netherlands
Xiaoliang Gong
Xiaoliang Gong
East China Normal University
China
Yang Xiang
Yang Xiang
Peking Union Medical College Hospital
China
Changjun Jiang
Changjun Jiang
Anhui Agricultural University
China
Xiaolin Zhou
Xiaolin Zhou
Peking University
China

Hum Brain Mapp 2015 Dec 29;36(12):5233-51. Epub 2015 Sep 29.

Center for Brain and Cognitive Sciences and Department of Psychology, Peking University, Beijing, China.

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.

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December 2015
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