July 2013
Volume 13, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Neural representation of the bottom-up saliency map of natural scenes in human primary visual cortex
Author Affiliations
  • Cheng Chen
    National Engineering Lab for Video Technology and School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, P. R. China\nKey Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing 100871, P. R. China
  • Xilin Zhang
    Department of Psychology, Peking University, Beijing 100871, P. R. China\nKey Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing 100871, P. R. China
  • Tiangang Zhou
    State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, P. R. China
  • Yizhou Wang
    National Engineering Lab for Video Technology and School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, P. R. China\nKey Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing 100871, P. R. China
  • Fang Fang
    Department of Psychology, Peking University, Beijing 100871, P. R. China\nKey Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing 100871, P. R. China
Journal of Vision July 2013, Vol.13, 233. doi:10.1167/13.9.233
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    • Get Citation

      Cheng Chen, Xilin Zhang, Tiangang Zhou, Yizhou Wang, Fang Fang; Neural representation of the bottom-up saliency map of natural scenes in human primary visual cortex. Journal of Vision 2013;13(9):233. doi: 10.1167/13.9.233.

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

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Abstract

Zhang and colleagues recently showed that neural activities in V1 could create a bottom-up saliency map (Neuron, 73, 183-192, 2012). In that study, they used simple bar textures and a salient region was created by the orientation contrast between foreground and background bars. Here, we tested if their conclusion can generalize to complex natural scenes. Fifty natural images were selected from the internet based on the output of a prominent saliency model proposed by Itti and Koch (1998). The model predicted that all the natural images had a focal, lateral salient region, which was confirmed by a psychophysical experiment. In the experiment, to avoid top-down influences, each image was presented with a low contrast for only 50 ms and was followed by a high-contrast mask, which rendered the whole image invisible to subjects (confirmed by a forced-choice test). The Posner cueing paradigm was adopted to measure the spatial cueing effect (i.e. saliency) of the predicted salient region on an orientation discrimination task. A positive cueing effect was found and the magnitude of the cueing effect was consistent with the saliency prediction of the model. In a following fMRI experiment, we also used the masked natural scenes and measured BOLD signals responding to the predicted salient region (relative to the background). We found that the BOLD signal in V1, but not in other cortical areas, could well predict the cueing effect. These findings suggest that the bottom-up saliency map of natural scenes could be constructed in V1, providing further compelling evidence for the V1 saliency theory (Li, 2001).

Meeting abstract presented at VSS 2013

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