Visualization Gallery

Posted on Mar 4, 2018

One the things that I enjoy the most in science is to communicate the findings in beautiful figures. I believe scientific figures should be effective (i.e., leave an impression) and efficient (i.e., highlight the main story). Here are some examples of the images that I have created (or helped to create) for research and teaching. Click on the images for brief explanations.

In 1977, mathematician Bill Gospher developed an algorithm for doing computation with continued fractions. I wrote some code to illustrate how it works. (c) Hsin-Hao Yu — Bill Gospher's algorithm

This image communicates 3 pieces of information about data collected in the visual cortex: the shape of the receptive field (shaded in blue), the fine details about the neuronal responses (individual histograms), and result of a model fitted to the data (the oval-shaped contour). Published in Yu et al. (2013) The Journal of Neuroscience 33, 12479-12489. — A 'receptive field' map

This image illustrates the dynamics of a computational model to explain the formation of maps in the visual cortex. Published in Yu et al. (2020) Science Advances 6, EAAZ8673 — The unfolding of the elastic net

I simulated the movement of the sun in the sky, to communicate a unique sundial installed on the campus of Monash University. (c) Hsin-Hao Yu — The trajectory of the sun in the sky.

An illustrations of the anatomical subdivisions of the medial surface of the primate brain. 3D models of the cortical areas were traced from histological images and rendered in ParaView (In Yu et al., 2012, Current Biology 22: 1351-1357) — Areas in the medial surface of the posterior brain

Results of a brain mapping experiment. The polygons are the parts of the visual field encoded by neurons in the visual cortex. The are plotted on the sphere and on projections to the 2D plane. In Yu et al., (2015) Neuroscience Research 93:47-61. — Representation of the visual field

This matrix shows the strength of connections among areas in the cortex (In Reser et al., 2013. Cerebral Cortex 23, 1901-1922) — Patterns of brain connectivity

This figure illustrates a particularly complex topological map in the visual cortex. The colors and contours represent the coordinates of the visual space. (In Yu et al. 2020. Science Advances) — Complex topological maps in the visual cortex

Connection tracing is an anatomical technique in neuroscience to reveal brain structures that are connected to each other. This figure illustrates the result of a tracing study by plotted the density of the labeled neurons on a flattened representation of the cortical surface. In Rosa et al. (2009) Journal of Neuroscience 29: 4548-4563. — Visualiazing tracer injection data

This figure illustrating brain areas that are expanded in the course of evolution was used as the cover of the 18 September 2013 issue of The Journal of Neuroscience. In Chaplin et al. (2013) Journal of Neuroscience 33: 15120-15125. — Comparing the cortical expansions across different species

This is a visuotopic map of the primary visual cortex of the marmoset. Visualized with ParaView using the data published in Chaplin, Yu & Rosa (2013) Journal of Comparative Neurology 521: 1001-1019. Unpublished figure. (c) Hsin-Hao Yu. — A map of the primary visual cortex

Model neurons for the detection of image motion, illustrated in the 3D Fourier space. Unpublished figure. (c) Hsin-Hao Yu. — Models of image motion detectors

This figure was created to illustrate the structure of the 3D Fourier space of image motion. Unpublished figure. (c) Hsin-Hao Yu. — The Fourier representation of image motion

Volumetric rendering of magnetic resonance imaging data. Unpublished figure. (c) Hsin-Hao Yu. — Volumetric rendering of the brain

I used the Fisher-Bingham distribution to analyze data parameterized on the sphere. Unpublished figure. (c) Hsin-Hao Yu. — Data analysis on the sphere

This is an abstract representation of the response properties of a visual neuron in a low dimensional space. Unpublished figure. (c) Hsin-Hao Yu. — Modeling the behaviors of visual neurons

A simulation of two types of aspheric lens. Unpublished figure. (c) Hsin-Hao Yu. — Optical simulations

The patches represent anatomical areas in the brain of the marmoset. In Paxinos et al. (2011) The Marmoset Brain in Stereotaxic Coordinates. — An altas of the marmoset brain

This figure illustrates a geodesic (shortest path) on a model of the primary visual cortex. Unpublished figure. (c) Hsin-Hao Yu. — Quantifying cortical maps with differential geometry

I created this figure to explain to students how the visual space is represented in the visual cortex. Unpublished figure (c) Hsin-Hao Yu. — An illustration of cortical magnification

An illustration of how the visual space is represented in the visual cortex. Unpublished figure (c) Hsin-Hao Yu. — An illustration of cortical magnification

Basis functions for image reconstruction. Unpublished figure (c) Hsin-Hao Yu — Image analysis

Animations

This video illustrates the evolution of a self-organization model of maps in the visual cortex. See this paper.

This movie illustrates the evolution of a self-organization model defined on a non-Euclidean surface. See this post.

Fourier analysis says that you don’t necessarily need Leonardo da Vinci’s mastery of the brush to paint Mona Lisa. All that you need is knowing how to paint stripes. This video demonstrates that by adding up Fourier components, you can reconstruct the Mona Lisa. I made this for a lecture in computational neuroscience. See this post.

This is a simulation of a sundial installed on the northern wall of the Campus Centre of Monash University (Clayton, Australia). The sundial was designed by mathematician Carl Moppert. To learn more about the sundial, see this post.