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Some of the topics in neuroscience that I have worked on:

Current Research: Machine Learning and Functional Brain Imaging

In 2016, I was awarded research grants from the Australian Research Council and the National Health and Medical Research Council to use machine learning methods on the analysis of neurophysiolgical data. In addition, I am also working on new methodologies to imagine the activities of the visual cortex. Initial findings will be published in the near future.

Mapping the Visual Cortex

In 2012, I identified a new component of the visual cortex called area prostriata using electrophysiological recordings. This area is weird. It seems to devote most of its resource to the processing of information in the far peripheral visual field (close to the edge of vision), and it seems to be a short-cut for visual information be integrated with non-visual areas in the brain, bypassing most of hierarchy of the visual cortex.

  • My paper: Yu et al. (2012) A specialized area in limbic cortex for fast analysis of peripheral vision. Current Biology 22, 1351-1357. [link]
  • The area was confirmed in the human brain using fMRI in 2017. See Mikellidou et al. (2017) Area Prostriata in the Human Brain. Current Biology 27, 3056-3060. [link]
  • Commentaries on area prostriata:
    • Tamietto & Leopold (2018) Visual Cortex: The Eccentric Area Prostriata in the Human Brain. Current Biology 28, pR17–R19. [link]
    • Rockland (2012) Visual System: Prostriata — A Visual Area Off the Beaten Path. Current Biology 22, pR571-R573. [link]
  • There is (interestingly) a prostriata hashtag on twitter: #prostriata.

Plasticity and Development

From 2012 to 2017, I conducted a long-term study about how the visual pathways are altered by brain injuries, especially at the early stages of development. This research is related to a mysterious phenomenon called blindsight.

  • Publications:
    • Yu et al. (2018) Robust visual responses and normal retinotopy in primate lateral geniculate nucleus following long-term lesions of striate cortex. Journal of Neuroscience 38, 3955-3970. [link]
    • Yu et al. (2013) Visually evoked responses in extrastriate area MT after lesions of striate cortex in early life. Journal of Neuroscience 33, 12479-12489. [link]


My collaborator Tristan Chaplin and I tried to answer the question: do we have big brains because we are smarter? I wanted to publish the result under the title “Larger before Smarter”, but that probably was too cute. I also co-authored a book chapter on this topic.

  • Chaplin, Yu , Soares, Gattass, Rosa (2013) A conserved pattern of differential expansion of cortical areas in simian primates. Journal of Neuroscience 33, 15120-15125. [link]
  • Chaplin, Rosa, Yu (2016) Scaling up the simian primate cortex: a conserved pattern of expansion across brain sizes. In Evolution of Nervous Systems, 2nd edition (Eds. Kaas, JH), Vol. 4, Academic Press. [link]

Computational Neuroscience

My main interest is the representation of the trajectories of moving images in the visual cortex.


  • Davies, Chaplin, Rosa, Yu (2016) Natural motion trajectory enhances the coding of speed in primate extrastriate cortex. Scientific Reports 6, e19739. [link].
  • Yu et al. (2010) Spatial and temporal frequency in striate cortex: functional uniformity and specializations related to receptive field eccentricity. European Journal of Neuroscience 31, 1043-1062. [link].

Peripheral Vision

The biggest difference between human vision and computer vision is that human vision is spatially non-uniform: we have a fovea which is specialized for high acuity. But the functional implications of this important difference are not clear. A review article I wrote might be useful for those interested in this topic.


  • Computational anatomy and digital atlasing: I contributed to the early development of the Marmoset Brain Architecture Project.
  • A significant part of my work has been done with a display system that projects panoramic patterns to a spherical surface. The design and implementation is described in here.