Elizabeth Zavitz, photograph

Elizabeth Zavitz, PhD

I study the brain from a computational perspective. I'm interested in how the information in a visual scene is transformed and represented across neural populations. My research focuses on how spatial and temporal context affect encoding using a combination of behavioural, computational, and electrophysiological methods.

Research Articles

Feizpour A., Majka P., Chaplin T.A., Rowley D.P., Yu, H.-H., Zavitz, E., Price, N.S.C., Rosa, M.G.P., Hagan, M.A. (2021). Visual responses in the dorsolateral frontal cortex of marmoset monkeys, Journal of Neurophysiology, 125(1): 296-304.

Yu, H.-H., Rowley, D.P., Price, N.S.C., Rosa, M.G.P. & Zavitz, E. (2020). A twisted visual field map in the primate cortex predicted by topographic continuity, Science Advances, 6(44): eaaz8673.

Zavitz, E. & Price, N.S.C. (2019). Weighting neurons by selectivity produces near optimal population codes, Journal of Neurophysiology, 121(5): 1924-1937

Ghodrati, M., Zavitz, E., Rosa, M.G.P. & Price, N.S.C. (2019). Contrast and luminance adaptation alter neuronal coding and perception of stimulus orientation. Nature Communications, 10(1), 941.

Zavitz, E. & Price, N.S.C. (2019). Understanding sensory information processing through simultaneous multi-area population recordings, Frontiers in Neural Circuits, 12(115).

Zavitz, E., Yu, H.-H., Rosa, M.G.P. & Price, N.S.C. (2019). Correlated variability in the neurons with the strongest tuning improves direction coding, Cerebral Cortex, 29(2): 615-626.

Zavitz, E., Yu, H.-H., Rowe, E.G., Rosa, M.G.P. & Price, N.S.C. (2016). Rapid Adaptation Induces Persistent Biases in Population Codes for Visual Motion, Journal of Neuroscience, 36(16): 4579-4590.

Featured in:

Zavitz, E. & Baker, C.L. (2014). Higher-order image structure enables boundary segmentation in the absence of luminance or contrast cues, Journal of Vision, 14(4), 1-14.

Zavitz, E. & Baker, C.L. (2013). Texture sparseness, but not local phase structure, impairs second-order segmentation, Vision Research, 91, 45-55.

Arsenault, E., Yoonessi, A. & Baker, C. (2011). Higher order texture statistics impair contrast boundary segmentation. Journal of Vision, 11(10), 1-15.


Kermani M., Zavitz, E., Oakley, B.H., Price, N.S.C., Hagan, M.A., Wong, Y.T.. Long-range neural coherence encodes stimulus information in primate visual cortex. biorXiv.

Visual Information Exhibit

I designed an exhibit "From Noise to Meaning: How Visual Information Makes Sense" that shows how different types of visual information combine to produce our perceptual experience.

Please note that to view the video properly, it must be downloaded to a computer and played in a media player. Online video streaming relies on compressed video signals that leverage the characteristics of natural images - characteristics that are deliberately removed from most of this video.

The video is available for download here.

The exhibition record for the library is available here.

Over our lifetimes, we get to see a varied collection of images that reflect the huge diversity of things around us. In reality, we are only likely to experience a very small subset of possible images. The things we end up seeing are not only constrained, but constrained in very predictable ways. Objects tend to have continuous edges and surfaces, and are constructed in ways consistent with the laws of the physical world. We also tend to see fewer, larger objects close to us, rather than the many smaller objects that are further away. These constraints produce regularity that the brain can take advantage of to improve how it processes visual information.

Visual information comes in two forms: energy, and spatial structure. The ‘energy’ is the combination of frequencies and proportions present in the image, analogousto the combination of notes played simultaneously by an orchestra, or the palette of colours available to a painter. Spatial structure refers to how that energy is distributed across the space of an image: it is the melody the orchestra plays, or the scene the painter creates.

In this exhibit, I illustrate some of the regularities in which our brains specialise. The video begins with static-like noise: there is no structure. Gradually, the noise beginsto look cloudy as the palette of energies is made more consistent with what we see in the natural world. The noise thins until the image becomes sparse and individual patterns emerge. The patterns then arrange themselves into elongated contours, which snap into focus as the energy across different spatial scales aligns at one point in space. Notice how the viewing experience becomes more comfortable as the visual information is arranged in increasingly natural ways and becomes more consistent with what the brain anticipates.

The regularities presented here have shaped the nature of our visual brains on both evolutionary and developmental timescales, and can provide an important lever towards understanding the inner working of neural networks.

Book Chapters

Zavitz, E., Rosa, M.G.P. & Price, N.S.C. (2016). Primate Visual Cortex in Reference Module in Neuroscience and Biobehavioral Psychology

Price, N.S.C., Zavitz, E. & Born, R.T. (2016). Representation of Movement in Reference Module in Neuroscience and Biobehavioral Psychology


"Stimulus statistics restructure correlated variability within and between visual areas" CoSyNe (Lisbon, Portugal, February 2019) [poster PDF]

"Network structure within and between marmoset V1 and MT facilitates natural image coding" Society for Neuroscience Annual Meeting (San Diego, USA, November 2018) [poster PDF]

"Population codes in V1 and MT are optimised for the structure of natural images" Society for Neuroscience Annual Meeting (Santorini, Greece, June 2018) [poster PDF]

"Population codes in V1 and MT are optimised for the structure of natural images", Systems and Computational Neuroscience Down Under (Brisbane, Australia, December 2017). [poster PDF]

"Task- and time-dependence of population codes for motion in marmoset MT", Society for Neuroscience Annual Meeting (San Diego, USA, November 2016). [poster PDF]

"Adaptation survives intervening stimulation in area MT", Society for Neuroscience Annual Meeting (Washington DC USA, November 2014). [poster PDF]

"Higher-order texture statstics influence and enable segmentation in synthetic and natural texures", Bosch Institute Annual Meeting (Sydney, Australia, July 2013). [poster PDF]

"Segmentation of boundaries defined by natural and naturalistic textures", Sensory Coding and Natural Environment (Klosterneuberg, Austria, July 2013). [poster PDF]

Last updated: 4 March, 2021