Xin Huang

Position title: Associate Professor Ph.D., Brown University


Phone: Phone: (608) 265-2744 | Fax: (608) 265-5512

RESEARCH INTERESTS - Neural basis of vision and visually guided behavior.

Xin Huang

Huang-Xin - 1

Research Description

Human activity is greatly enriched by vision. Relying on our versatile visual system, we can cruise through morning traffic, judge the trajectory of a fast-approaching tennis ball and quickly return it. Vision also provides a major portion of our subjective sensory experience. We enjoy seeing the opulent sky color at dusk and admire the vibrant energy of van Gogh’s Starry Night. Because of the importance of vision, visual disorders have devastating consequences.

Our laboratory seeks to understand the neural mechanisms underlying visual perception and visually guided behavior.  Visual information is represented and processed by a large number of neurons distributed across dozens of brain areas, structured in a hierarchical and parallel manner. Each of these neurons is sensitive to certain features of the visual scene and has a spatially constrained “view” of the world through its receptive field. As information flows deeper into the brain, neural representations transform from pixel-based to object-based, and from sensory to more cognitive and premotor – reflecting the processes of attention, decision-making, and motor planning.

The research in our laboratory aims to address the following questions: 

  • To understand the neural processes underlying perceptual organization. Specifically, a) How does the visual system integrate multiple stimulus features to generate the perceptual whole of an object? b) How does the visual system segregate multiple objects from each other and segregate a figural object from its background to achieve segmentation?  c) What is the role of selective attention in perceptual organization?
  • How does the visual system transform information along the visual hierarchy to generate perception and guide behavior?
  • What are the functional roles of massive and widespread feedback connections in the visual system?
  • What are the neural mechanisms underlying selective attention?
  • To understand the neural basis of visual awareness. What distinguishes the neural representations that do or do not give rise to visual awareness?
  • To understand the principles and rationale of population neural coding.
  • To understand the neural circuit mechanisms underlying canonical neural computations.

To investigate these questions, we use integrated approaches of modern electrophysiology, psychophysics, computational modeling, and behavioral tasks involving discrimination, attention, and decision-making. We are also developing and applying calcium imaging and optogenetic methods for circuit interrogation and manipulation.

Interested students can apply to the following Ph.D. programs:

Neuroscience Training Program
Biophysics Interdisciplinary Program

Opportunities for graduate study are available in the lab. Students who have a science and/or engineering background and strong motivation to uncover the mysteries of the brain are encouraged to apply. For inquiries, please email

Selected Publications and Pre-Prints

    • Chakrala A, Xiao J, Huang X. (2023). The role of binocular disparity in the neural representation of multiple moving stimuli in the visual cortex. bioRxiv. doi:
    • Huang X, Ghimire B, Chakrala AS, Wiesner S. (2023). Neural coding of multiple motion speeds in visual cortical area MT. bioRxiv. doi: Under peer review at eLife.
    • Manning TS, Alexander E, Cumming CG, DeAngelis GC, Huang X, and Cooper EA. (2024). Transformations of sensory information in the brain suggest changing criteria for optimality. PLOS Computational Biology. Published: January 11, 2024.
    • Wiesner S, Baumgart IW, Huang X. (2020). Spatial arrangement drastically changes the neural representation of multiple visual stimuli that compete in more than one feature domain. Journal of Neuroscience. 40(9):1834-1848. Epub 2020 Jan 14.
      Abstract | Full Text
    • Huang W, Huang X, Zhang K. (2017). Information-theoretic interpretation of tuning curves for multiple motion directions. Proceeding of 51st Annual Conference on Information Sciences and Systems (CISS). doi: 10.1109/CISS.2017.7926142.
      Abstract | PDF
    • Chuang J, Ausloos EC, Schwebach CA, Huang X. (2016). Integration of motion energy from overlapping random background noise increases perceived speed of coherently moving stimuli. Journal of Neurophysiology. 116(6):2765-2776. doi: 10.1152/jn.01068.2015.
      Abstract | PDF| Journal Highlight
    • Xiao JB, Huang X. (2015). Distributed and dynamic neural encoding of multiple motion directions of transparently moving stimuli in cortical area MT. Journal of Neuroscience, 35(49): 16180-198.
      Abstract | PDF
    • Xiao JB, Niu YQ, Wiesner S, Huang X. (2014). Normalization of neuronal responses in cortical area MT across signal strengths and motion directions. Journal of Neurophysiology. 112(6):1291-306. Epub 2014 June 3. doi:10.1152/jn.00700.2013.
      Abstract | PDF
    • Vokoun C, Huang X, Jackson M, and Basso M. (2014). Response normalization in the superficial layers of the superior colliculus as a possible mechanism for saccadic averaging. Journal of Neuroscience. 34(23):7976-87
      Abstract | PDF
    • Huang X, Lisberger SG. (2013). Circuit mechanisms revealed by spike-timing correlations in macaque area MT. Journal of Neurophysiology. 109:851-866. Epub 2012 Nov 14. doi:10.1152/jn.00775.2012. “Editor’s Choice” article.
      Abstract | PDF
    • Gaudio JL, Huang X. (2012) Motion noise changes directional interaction between transparently moving stimuli from repulsion to attraction. PLoS One. 7(11):e48649. doi:10.1371/journal.pone.0048649
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    • Huang X and Lisberger SG. (2009) Noise correlations in cortical area MT and their potential impact on trial-by-trial variation in the direction and speed of smooth pursuit eye movements. Journal of Neurophysiology, 101:3012-3030Motion Processing
      Abstract | PDF
    • Huang X, Albright TD, and Stoner GR. (2008) Stimulus-dependency and mechanisms of surround modulation in cortical area MT. Journal of Neuroscience, 28(51):13889-906.
      Abstract | PDF
    • Huang X and Paradiso MA (2008) V1 response timing and surface filling-in. Journal of Neurophysiology, 100: 539-47.
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    • Huang X, Levine S, and Paradiso MA. (2008) Rebounding V1 activity and a new visual aftereffect. Journal of Vision, 8(3):25, 1-10.
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    • Churchland AK, Huang X, Lisberger SG (2007). Responses of neurons in the medial superior temporal visual area (MST) to apparent motion stimuli in macaque monkeys. Journal of Neurophysiology. 97: 272-282.
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    • Huang X, Albright TD, and Stoner GR.(2007) Adaptive surround modulation in cortical area MT. Neuron, 53: 761-770.
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    • Huang X and Paradiso MA (2005) Background changes delay information represented in macaque V1 neurons. Journal of Neurophysiology, 94: 4314-30.
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    • Huang X, Blau S, and Paradiso MA(2005) Background changes delay the perceptual availability of form information. Journal of Neurophysiology, 94: 4331-43.
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    • Huang X, MacEvoy SP, Paradiso MA (2002). Perception of brightness and brightness illusions in the macaque monkey. The Journal of Neuroscience. 22(21): 9618-25
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