August 2014
Volume 14, Issue 10
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Brain signatures of reward-dependent bias in visual attention
Author Affiliations
  • Iris Wiegand
    Center for Visual Cognition, Department of Psychology, University of Copenhagen
  • Carsten Nielsen
    Center for Visual Cognition, Department of Psychology, University of Copenhagen
  • Anders Petersen
    Center for Visual Cognition, Department of Psychology, University of Copenhagen
  • Mads Dyrholm
    Center for Visual Cognition, Department of Psychology, University of Copenhagen
  • Claus Bundesen
    Center for Visual Cognition, Department of Psychology, University of Copenhagen
Journal of Vision August 2014, Vol.14, 506. doi:10.1167/14.10.506
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      Iris Wiegand, Carsten Nielsen, Anders Petersen, Mads Dyrholm, Claus Bundesen; Brain signatures of reward-dependent bias in visual attention. Journal of Vision 2014;14(10):506. doi: 10.1167/14.10.506.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

According to the Theory of Visual Attention (TVA), important visual features (features with a high valence) are processed more rapidly than unimportant ones. In the present study, we tested this assumption and assessed brain correlates of reward-dependent changes in visual processing by combining the formal framework of TVA with electrophysiology (EEG). We recorded EEG while participants completed a task in which accuracy of discriminating certain stimulus features was selectively associated with contingent monetary rewards. More specifically, the rewards for detecting Landolt ring gap locations on the diagonal and straight axes were varied across blocks, thereby abstracting valence from salience effects. We quantified performance using TVA-based fitting, and analyzed event-related potentials (ERP) and linear discriminant components to unveil brain mechanisms underlying behavioral changes related to reward. We found a higher processing rate for features associated with high reward relative to those associated with low reward. The behavioral effect was mirrored in multiple grand-average ERP modulations: The P1 was higher, and mid-latency central positivity was lower, when the to-be-discriminated feature's valence was high. A stronger medial frontal negativity (MFN) later in time was found for lower-rewarded features. The results suggest that sensory, attentional, and motivational processes contribute to the effects of reward on visual discrimination accuracy. On the single-trial level, we separated spatio-temporal components giving information about the dynamics of these processes. In accordance with TVA, we argue that a controlled setting of perceptual biases, such that important features are associated with stronger perceptual biases (β values), eases the encoding of features associated with high positive outcomes from early perceptual stages on.

Meeting abstract presented at VSS 2014

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