Zijiang J He, PhD

Professor and Distinguished University Scholar

Portrait of Zijiang He

Life Sciences Building, 306

(502) 852-6779

(502) 852-8904



Life Sciences Building, 350

(502) 852-3850

Visual Perception and Cognition Lab


  • B.S. in Biophysics (1978-1983), University of Science and Technology of China, China
  • M.S. in Neurobiology (1983-1986), Shanghai Institute of Physiology, Academia Sinica, China
  • Ph.D. in Physiological Optics & Neuroscience (1987-1990), University of Alabama at Birmingham, USA
  • Postdoctoral Training (December, 1990-July, 1994), Department of Psychology, Harvard University, USA

Research Interest

Visual Perception and Cognition

My research interest is in understanding how humans perceive visual objects and the spatial environment. The act of seeing is very complex; and discovering its underlying mechanisms demands a multidisciplinary approach that deals with a variety of issues associated with visual perception and cognition. In concert with this, while psychophysical methods and phenomenological observations are predominantly employed in my research, considerations from neuroscience and computational approaches are vigorously applied in the research design, data analysis and interpretation. Currently, my laboratory focuses on two major areas of research, which are summarized below.

Space Vision

The vivid 3-dimensional perception of the world around us begins with the processing of the 2-dimensional retinal images. How is this feat achieved? In particular, how does our brain process the 2-dimensional retinal information and endow it with the remarkable sensation of 3-dimensional depth? What assumptions or internal laws are implemented at the various neural processing stages to accomplish this? And where do these assumptions come from? To the last question, many researchers believe that they are related to the regularities or rules specified by our niche and ecology. Utilizing these regularities, our brain is able to reduce its coding redundancy and enhance its efficiency. Our research objectives are to reveal what external environmental information is extracted for space perception, and to learn the assumptions and computational steps the brain uses to derive the 3-dimensional perceptual space as it operates on the external information. We currently focus on studying space vision in the intermediate distance range. Our psychophysical research employs various methods (perceptual report, visually directed and guided actions, eye movement and locomotion recordings, etc.) to measure human subjects’ performances both in the real space and virtual reality (VR) environments. Capitalizing on the relatively recent VR technology not only provides us with a more convenient means to manipulate the visual scenes, but also allows us to create novel visual space to learn how the human visual system adapts to new spatial environments. In this way, we can also discover how the visual system "recognizes" new environmental regularities and implements them as rules.

Mechanisms of Middle Level Vision

The confluence of scientific achievements by the neuroscience, psychophysical, and computational research communities have greatly advanced our understanding of the coding of visual information at the early stage of the visual pathway. By taking advantage of this knowledge, and building on it, our recent research focuses on the question of how visual information is processed at a yet later stage of the visual pathway. This stage is the surface representation level, which serves as the critical stage between the early cortical filtering level and the late object recognition level. Our understanding of the surface representation level is in its infancy and many questions are yet to be answered. Among the questions my laboratory is exploring are: How are the outputs of the early cortical filtering level integrated to form surface representations, and what are the rules used in the integration process? How much does the surface representation level contribute to our immediate perception of the visual world? How does visual information at the middle level affect object representation? What roles do visual attention and memory mechanisms play in the processing of visual information between the surface representation level and object recognition level? Finding these answers are important steps toward understanding the workings of middle level vision.

Selected Publications

  1. Zhou, L., Deng, C., Ooi, T. L. & He, Z. J. (2016). Attention modulates perception of visual space. Nature Human Behaviour, 1, doi:10.1038/s41562-016-0004.
  2. Zhou, L., Ooi, T. L. & He, Z. J. (2016). Intrinsic spatial knowledge about terrestrial ecology favors the tall for judging distance. Science Advances, 2(8), e1501070. DOI: 10.1126/sciadv.1501070.
  3. Xu, J. P., He, Z. J. & Ooi, T. L. (2010). Effectively reducing sensory eye dominance with a push-pull perceptual learning protocol. Current Biology, 20, 1864-1868.
  4. Su, Y., He, Z. J., & Ooi, T. L. (2009). Coexistence of binocular integration and suppression determined by surface border information. Proceedings of National Academy of Sciences (USA), 106 (37), 15990-15995.
  5. Ooi, T. L. & He, Z. J. (2007). A distance judgment function based on space perception mechanisms – revisiting Gilinsky’s equation. Psychological Review, 144(2), 441-454.
  6. Wu, B., Ooi, T. L., & He, Z. J. (2004). Perceiving distance accurately by a directional process of integrating ground information. Nature, 428, 73-77.
  7. Ooi, T. L., Wu, B., & He, Z. J. (2001). Distance determined by the angular declination below the horizon. Nature, 414, 197-200.
  8. Sinai, M. J., Ooi, T. L., & He, Z. J. (1998). Terrain influences the accurate judgement of distance. Nature, 395, 497-500.
  9. He, Z. J. & Nakayama, K. (1995). Visual attention to surfaces in three-dimensional space. Proceedings of National Academy of Sciences (USA), 92, 11155-11159.
  10. He, Z. J. & Nakayama, K. (1994). Apparent motion determined by surface layout not by disparity or by 3-dimensional distance. Nature, 367, 173-175.
  11. He, Z. J. & Nakayama, K. (1992). Surfaces vs. features in visual search. Nature, 359, 231-233.

Some Recent Publications

  1. Ooi, T.L., & He, Z.J. (2020). Sensory Eye Dominance: Relationship Between Eye and Brain. Eye and Brain, 12, 25-31. http://doi.org/10.2147/EB.S176931.
  2. Han, C., He, Z.J., & Ooi, T.L. (2019). Effect of interocular contrast difference on stereopsis in observers with sensory eye dominance. Invest Ophthalmol. Vis Sci., 60, 3178–3186. https:// doi.org/10.1167/iovs.18-26112.
  3. Han, C., He, Z.J., & Ooi, T.L. (2018). On sensory eye dominance revealed by binocular integrative and binocular competitive stimuli. Invest Ophthalmol. Vis Sci., 59, 5140–5148. https://doi.org/10.1167/iovs.18-24342.
  4. He, Z. J., Ooi, T. L., & Su, R. Y. (2018). Perceptual mechanisms underlying amodal surface integration of 3-D stereoscopic stimuli. Vision Research, 143, 66–81. https://doi.org/10.1016/j.visres.2017.10.005
  5. Ooi, T. L. & He, Z. J. (2015). Space perception of strabismic observers in the real world environment. IOVS, 56, 1761-1768. doi:10.1167/iovs.14-15741.
  6. Wu, J., Zhou, L., Shi, P., He, Z. J. & Ooi, T. L. (2015). The visible ground surface as a reference frame for scaling binocular depth of a target in midair. Journal of Experimental Psychology: HPP., 41(1), 111-126 . doi: 10.1037/a0038287.
  7. Wu, J., He, Z. J. & Ooi, T. L. (2014). The visual system’s intrinsic bias influences space perception in the impoverished environment. Journal of Experimental Psychology: HPP., 40, 626-628. doi: 10.1037/a0033034.
  8. Zhou, L., He, Z. J. & Ooi, T. L. (2013). The visual system’s intrinsic bias and knowledge of size mediate perceived size and location in the dark. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1930-1942. doi: 10.1037/a0033088.
  9. Ooi, T. L., Su, Y. R., Natale, D. M. & He, Z. J. (2013). A push-pull treatment for strengthening the ‘lazy eye’ in amblyopia. Current Biology, 23(8), R309-310.
  10. Xu, J.P., He, Z. J. & Ooi, T. L. (2012) Further support for the importance of the suppressive signal (pull) during the push-pull perceptual training. Vision Research. 61, 60-69. http://dx.doi.org/10.1016/j.visres.2012.01.003
  11. Xu, J. P., He, Z. J. & Ooi, T. L. (2012). Push-pull training reduces foveal sensory eye dominance within the early visual channels. Vision Research. 61, 48-59. doi:10.1016/j.visres.2011.06.005
  12. Xu, J. P., He, Z. J. & Ooi, T. L. (2012). Perceptual learning to reduce sensory eye dominance beyond the focus of top-down visual attention. Vision Research. 61, 39-47. doi:10.1016/j.visres.2011.05.013
  13. Xu, J.P., He, Z. J. & Ooi, T. L. (2011). A binocular perimetry study of the causes and implications of sensory eye dominance. Vision Research. 51, 2386–2397.
  14. Su, R. Y., He, Z. J., & Ooi, T. L. (2011). Revealing boundary-contour based surface representation through the time course of binocular rivalry. Vision Research, 51, 1288–1296.
  15. Su, R. Y., He, Z. J., & Ooi, T. L. (2011). Seeing grating-textured surface begins at the border. Journal of Vision, 11(1):14, 1–14, http://www.journalofvision.org/content/11/1/14, doi:10.1167/11.1.14.
  16. Su, R. Y., He, Z. J., & Ooi, T. L. (2010). The magnitude and dynamics of interocular suppression affected by monocular boundary contour and conflicting local features. Vision Research, 50, 2037-2047.
  17. Su, R. Y., He, Z. J., & Ooi, T. L. (2010). Boundary contour based surface integration affected by color. Vision Research, 50, 1833–1844.
  18. Xu, J. P., He, Z. J. & Ooi, T. L. (2010). Surface boundary contour strengthens image dominance in binocular competition. Vision Research, 50, 155–170.
  19. Su, Y., He, Z. J., & Ooi, T. L. (2010). Surface completion affected by luminance contrast polarity and common motion. Journal of Vision, 10, 1-14, http://journalofvision.org/10/3/5/, doi:10.1167/10.3.5.

Courses Taught Often

  • Sensation and Perception
  • Research Design and Method