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Clayton Hickey, Daniel Kaiser, Marius Peelen; Neural mechanisms of incentive salience in naturalistic human vision. Journal of Vision 2015;15(12):562. doi: 10.1167/15.12.562.
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What role does reward play in real-world human vision? Reward coding in the midbrain is thought to cause the rapid prioritization of reward-associated visual stimuli. However, existing evidence for this incentive salience hypothesis in vision is equivocal, particularly in naturalistic circumstances, and little is known about underlying neural systems. We used human fMRI to test the idea that reward will prime perceptual encoding of naturalistic visual stimuli and to identify the neural mechanisms underlying this function. Twenty participants detected examples of cued object categories - trees, cars, or people - in briefly presented images of cityscapes and landscapes. For each participant, one category of stimuli was special: when this object was the cued target, correct detection of a category example resulted in a cash payout. Using multivoxel pattern analysis we found that visual cortex carried more information about such reward-associated targets than reward-neutral targets. In contrast, when participants were cued to search for one of the reward-neutral categories, but the scene contained an example of the reward-associated category as distractor, encoding of information about the reward-associated stimulus was strongly suppressed. The strength of this suppression could be predicted by the magnitude of distractor-evoked activity in the dopaminergic midbrain and a connected cortical network, as well as by participant scores on a personality inventory indexing trait reward sensitivity. Examples of a reward-associated object category thus become visually salient, creating the need for attentional suppression when they are task irrelevant. The dopaminergic midbrain appears to mediate this effect, suggesting an interaction between the neural systems responsible for reward processing and visual perception in the human brain.
Meeting abstract presented at VSS 2015
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