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Glyn Humphreys, Jie Sui; Why the self stands out: Self conditioning to sensory stimuli alters perceptual salience. Journal of Vision 2013;13(9):941. doi: 10.1167/13.9.941.
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© ARVO (1962-2015); The Authors (2016-present)
Human perceptual learning is associated with slow-acting changes in the perceptual salience of stimuli. Here we present evidence showing that, in contrast to this, conditioning of a self-label to sensory stimuli produces ultra-fast alterations in the perceptual salience of the stimuli, changing the associated neural response . Using this self conditioning approach, we had participants associate shapes with either themselves or a friend, over just a short run of training trials. Subsequently the shapes had to be identified in hierarchical (global-local) forms. We first demonstrated effects of perceptual salience produced by blurring the shapes (to enhance global salience) and by introducing color differences between high-contrast local shapes (to enhance local salience). Response efficiency was reduced when the target had low salience and the distractor at the other level had high salience. Strikingly, this effect of perceptual salience was replicated when the original shapes were ‘tagged’ by associating to the self – response efficiency to a shape associated with an unfamiliar person was reduced when the distractor was associated with the self. This effect was not found for stimuli conditioned to another familiar person (best friend). Using fMRI we showed that the presence of a self conditioned distractor also increased activation in the left posterior parietal cortex, linked previously to the suppression of perceptually salient distractors (Mevorach et al., J. Cog. Neurosci., 2010). The results show that the conditioning of self-related information to sensory stimuli rapidly modulates visual perception, and the effects are modulated using similar neural processes to the effects of perceptual saliency. The data are consistent with social context affecting the way we see the world.
Meeting abstract presented at VSS 2013
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