August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Training-induced attentional bias alters the appearance of both trained and untrained stimuli
Author Affiliations
  • Sirawaj Itthipuripat
    Neurosciences Graduate Program
  • Kai-Yu Chang
    Department of Psychology, University of California, San Diego
  • Isabel Asp
    Department of Psychology, University of California, San Diego
  • John Serences
    Neurosciences Graduate Program
Journal of Vision September 2016, Vol.16, 1103. doi:10.1167/16.12.1103
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      Sirawaj Itthipuripat, Kai-Yu Chang, Isabel Asp, John Serences; Training-induced attentional bias alters the appearance of both trained and untrained stimuli. Journal of Vision 2016;16(12):1103. doi: 10.1167/16.12.1103.

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      © 2017 Association for Research in Vision and Ophthalmology.

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Abstract

Perceptual learning can have a direct impact on the perception of task-specific stimuli, and these effects can impact information processing both with and without awareness (Di Luca et al., 2010; Haijiang et al., 2006). In addition, the exogenous capture of spatial attention has also been shown to enhance the perceived contrast of a stimulus (Carrasco et al., 2004). Given these two sets of findings, we investigated whether training subjects to endogenously attend can induce changes in stimulus appearance and whether such an effect is stimulus-specific. We show that five days of training in an orientation discrimination task can alter the perceived contrast of grating stimuli at the trained compared to untrained locations. Moreover, these training-induced changes in perceived contrast transferred to influence the perception of other stimuli that were not part of the training set. Our results suggest that learning shapes the allocation of attentional priority to different locations in the visual field, and that these interactions between learning and attention can produce changes in perception in a non-stimulus-specific manner.

Meeting abstract presented at VSS 2016

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