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  • Vision & Consciousness

In visual perception, the ultimate goal is to understand how we see anything. We do not understand what visual consciousness is and most of visual processing appears to be unconscious. The first step in understanding these questions is to investigate the differences between conscious and unconscious states of visual processing. As one example, we use electrical stimulation of the human brain in epileptic patients (temporary electrodes due to clinical reason only) and investigate causal links between brain areas and perception. This research is supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korean government (MOST, No. M10644020001-06N4402-00110).

  • Blake, R., Tadin, D., Sobel, K. V., Raissian, T. A., & Chong, S. C. (2006). Strength of early visual adaptation depends on visual awareness. Proceedings of the National Academy of Sciences, 103, 4783-4788.
  • Shin, K., Stolte, M., & Chong, S. C. (2009). The effect of spatial attention on invisible stimuli. Attention, Perception, & Psychophysics, 71 (7), 1507-1513.

  • Statistical processing in Vision

Our environment contains lots of redundant information. Given the limited capacity of our visual system, it is important to process this massive information efficiently and economically. One example of this efficient processing is the automatic statistical analysis of a visual scene. Our lab investigates the mechanism of statistical processing in the brain, particularly focusing on the computation of the mean size of objects in visual arrays. This research is supported by the Korea Research Foundation Grant funded by the Korean government (MOEHRD, KRF-2007- 101039003-2007-8-0746).

  • Chong, S. C., & Treisman, A. (2003). Representation of statistical properties. Vision Research, 43, 393-404.
  • Chong, S. C., & Treisman, A. (2005 a). Attentional spread in the statistical processing of visual displays. Perception & psychophysics, 67,1-13.
  • Chong, S. C., & Treisman, A. (2005 b). Statistical processing: computing the average size in perceptual groups. Vision Research, 45, 891-900.
  • Chong, S. C., Shin, K. H., & Cho, S. H. (2008). Neural correlates of visual mean representation. Korean Journal of Cognitive Science, 19(1), 75-88.
  • Chong, S. C., Joo, S. J., Emmanouil, T. -A., & Treisman, A. (2008). Statistical processing: Not so implausible after all. Perception & Psychophysics, 70 (7), 1327-1334.
  • Im, H. Y. & Chong, S. C. (2009). Computation of Mean Size is Based on Perceived Size. Attention, Perception, & Psychophysics, 71 (2), 375-384.

  • Blind Spot

The blind spot is the area of the retina where the optic nerve exits the eye and no photoreceptors are present. Even though photoreceptors are absent in this area, we do not perceive an empty space. Understanding how we fill-in the blind spot can help us to understand the mechanism of surface perception. Furthermore, it can help us to understand visual consciousness because filled-in surfaces are the product of our perception rather than physical reality. This project began as a term project for an undergraduate-course (Information Processing Theory). Many contributions to this project came from the students who took the course.

  • Shin, I. J., Jung, D., Chong, S. C. (2007). Interocular Filling-in of the Blind Spot. The Korean Journal of Experimental Psychology, 19(3), 221-231.
  • Kim, J., Hong, S. J., Chong, S. C. (2007). Effects of Contrast and Relative Distance from Fovea of Surrounding Stimulus on Perceptual Completion at the Blind Spot. The Korean Journal of Experimental Psychology, 19(4), 329-342.
  • Park, K. M., Cha, O., Kim, S., Im, H. Y., Chong, S. C., (2007). The Influence of Depth Context on Blind Spot Filling-in. Korean Journal of Cognitive Science, 18(4), 351-370.