How Low Will I Stroop?

Okay, I admit that this is a somewhat lazy post. I’m still farily wrapped up in the Gordon Conference on Visualization, so you could interpret this as a less than stellar edition. My apologies. But after a day of more organic chemistry than I thought I could bear, I need to take a break!

So today’s post concerns a perennial favorite, the Stroop Effect, which is the cognitive delay that occurs when you try to read a color name printed in a different color—e.g., green or blue. (The above image comes from a Taiwanese web page about the effect, and I just found it rather amusing compared to the more obvious choice of listing words in English. “Look, ma, no stroop!”) Anyway, one of my fellow attendees pointed out that the Neuroscience For Kids site hosts a spiffy Stroop Effect Java Interactive that allows you to time yourself in reading off color names. Great stuff!

BTW, you can read Stroop’s original paper, if you’re interested, too.

And I’ll end with a shout out to the folks at GalaxyGoo! I show up in Kristin’s blog for today, so y’all can consider this just a wee bit of blogrolling…

Oh, and you can also listen to my podcast from the conference, hosted on the CalAcademy website.

Biochemical Art

I’m attending the Gordon Conference on Visualization in Science and Education, and this morning, we had a chance to hear (and see) David Goodsell from the Scripps Institute. Goodsell complements his research work with significant and influential dabbling in artwork. Above, you can see an image of blood serum taken from a collection of images he created for Biosite. His website describes the image as follows:

“Blood serum is shown in the picture, with many Y-shaped antibodies, large circular low density lipoproteins, and lots of small albumin molecules. The large fibrous structure at lower left is von Willebrand factor and the long molecules in red are fibrinogen, both of which are involved in blood clotting. The blue object is poliovirus.”

Goodsell preserves the shapes and relative sizes of the molecules while flattening the typical three-dimensional representations of molecules. He also represents the structures in cross section, using orthographic rendering to allow depicting large areas (large, that is, relative to the size of the molecules).

All of Goodsell’s images make good use of color, and I find the above image a particularly striking example. The poliovirus sticks out like a sore thumb (attractively composed asymmetrically within the frame), as of course it should. And it’s exceedingly pleasant to see depictions of molecules freed from the garish pseudocolor rainbow that seems to dominate the medium. Goodsell’s galleries include many more examples…

Evidently, Goodsell is also responsible for the “Molecule of the Month” at the RCSB Protein Data Bank (PDB). I haven’t taken a close look yet, but I plan to!

BTW, my home institution just started including me in a new category for the “Science in Action” podcast. Take a listen! I’ll have two more podcasts this week, mostly talking about the conference.

Stop and Go

The above image comes from a CNRS press release about the “double personality” of inhibitor neurons. Oh, and yes, the press release is in French. Sorry ’bout that. CNRS maintains an English site as well, but it lags several weeks behind the French site (shocking, I know).

Basically, researchers have discovered a chemical basis for the function of inhibitor neurons—neurons that seem to play a role in disorders such as paralysis and epilepsy. According to the new findings, the firing of a neuron (“stop” and “go,” as it’s described in the figure above) depends on the concentration of chloride ions, which is in turn controlled by proteins in the surface of the neuron.

To my eye, the visualization (presumably of actual data) communicates its message quite clearly. First off, it capitalizes on existing color associations with “stop” (red) and “go” (green), but it also does a nice job of highlighting specific regions of the neuron (n.b. “stop or go” and “stop or go”). A lot of information in a small space. The little diagram on the upper left is far too small for me to make out, but I’m guessing that it contains information that I would find interesting were I able to read it.

The red-green color scheme also seems to correlate with the use of bioluminescent tags in various samples. The book Aglow in the Dark: The Revolutionary Science of Biofluorescence taught me a wee bit about this field. Fascinating stuff.

Prehistoric Penguins

Now that I work at an institution that features penguins rather prominently, I find myself paying more attention to our tuxedoed friends. So it was hard to miss the Reuters story while I was browsing this morning.

According to the caption: “The late Eocene giant penguin Icadyptes salasi (right) and the middle Eocene Perudyptes devriesi (left) are shown to scale with the only extant penguin inhabiting Peru, Spheniscus humbolti (center).”

Even at this meager resolution, the illustration charms me with its depiction of the two smaller penguins gazing somewhat curiously at their larger relative—and the late Eocene fellow apparently opening his beak in amusement or mock surprise at his diminutive kin. I’m reading into it, obviously, but the illustration allows for a very friendly experience of information about the size and appearance of the animals.

Now, as Stephen Asma points out in his brilliant book, Stuffed Animals and Pickled Heads: The Culture and Evolution of Natural History Museums, the arrangement of specimens in a museum diorama can suggest misleading family groupings and social relationships and so forth. With the three species illustrated above, however, we’re seeing creatures from very different epochs placed side-by-side purely for purposes of comparison. To that end, the character and anthropomorphization of the subjects seems to me an added benefit.

I mean, it’s not exactly Cubee the Aggregate™, but hey…

So, kudos to artist Kristin Lamm. Nice work!

Cubee the Aggregate™

Right on the heels of marble-powered binary addition, I bring you Cubee the Aggregate™! The coloring books will delight youngsters. To quote the website, “Cubee and his aggregate friends will take children on a magical journey from Cubee’s birthplace in the neighborhood quarry to his new home in the schools, roads, and other structures that enrich our communities and lives.” Sounds, um, great. Magical, I mean. Maybe more like misguided.

And as my friend Jackie immediately pointed out, “Cubee’s not even a cube!”

A shout out to my friend Kelly for pointing this out to me.

Visualizing Addition

Matthias Wandel’s webpage describing his “binary marble adding machine” includes a YouTube clip as well, but for math geeks, the point should be clear from the above. Dropping marbles from the top of the gadget changes the state of the little toggles (a.k.a. “flipflops”), trapping some marbles and allowing others to fall through. Very kewl.

And one of the only physical demonstrations of binary addition I’ve ever seen. I mean, sure, there are applets online that will show you how to add binary numbers, but the wooden example above feels to me like a step that will bring you closer to understanding something like a circuit description of a binary adder. Perhaps someone with more intimate knowledge of computer circuits could draw some parallels… Do the wooden “flipflops” correspond to XOR gates?

Molecular Dominoes

A press release from the National Institute of Standards and Technology (NIST) uses the above image to describe “the growth of a layer of molecules as they gradually cover the surface of a small silicon rectangle.” Unfortunately, the image doesn’t seem to illustrate much at all.

As usual, I’ll quote the entire caption… “Schematic of the monolayer self-assembly process studied by the NIST/NCSU team. The silicon substrate is approximately 1 x 5 cm in dimensions. The source (left) is a mixture of organosilane (OS) molecules and parafin oil (to control the evaporation rate.) The whole system is enclosed in a Petri dish. The concentration of OS molecules is higher near the source and the ordering process initiates near this region. Molecules behind the advancing self-assembly front are relatively ordered, while molecules ahead of the front are engulfed and incorporated as the front reaches them. The molecules at the leading edge of the front are less ordered and this region becomes broader as the front advances—this is the key phenomenon measured in the experiment.”

Um, right.

Basically, to illustrate such a phenomenon, you’re probably better off using a series (i.e., at least a pair) of images to show, for example, an “advancing self-assembly front.” As it stands (or, in the case of the molecules on the right-hand side, leans), the image doesn’t really reveal the process very well.

Furthermore, if you read the accompanying press release, you find that the actual observations show irregularities in the advancing front, with variations in density that the simple model does not explain. So although the illustration receives top billing with the press release, it doesn’t actually show us what’s interesting about the press release!

An AVI available with the release claims to show “a mean field reaction-diffusion model of the monolayer self-assembly process,” but I couldn’t get the movie to play on my Macintosh.

Poor Label Placement

Image taken from an ESO press release about targeting dim objects near bright ones.

I was going to make just one snarky comment: namely, that one should be cautious where one places text in a contour plot… Or else one ends up with a small, circled “A” that misleadingly suggests the wrong location for an object.

Then I looked at the image and asked myself why the heck the contour lines were there at all (except to add visual confusion). As far as I can tell, they simply represent the same data shown by the pseudocolor image underneath. In other words, we’re being redundant on top of placing text poorly and haphazardly on the image.

Why do people insist on the entire freakin’ rainbow for their pseudocolor images? Is it because they’re trying to use up ink in their printer cartridges at an even rate? Is it because they can’t walk to their nearest public library and pick up an Edward Tufte book that will help set them straight?

Sigh. It’s been a long day. Time to go to another meeting…

Pull My Finger

New York Magazine recently posted “The Science of Gaydar” to its site, which uses the above figure to illustrate one of various physical attributes that are statistically correlated with sexual orientation (straight on the left, gay on the right, by the way). Others include fingerprint density, hair whorl direction, and handedness. With minimal captioning and added text, the magazine’s designers have created a sequence of simple, easy-to-understand images. Admittedly, it’s not exactly rocket science, but clarity and elegance go a long way in my book.

For example, note how the type in the above image guides you toward seeing which digit is longer. Placing the text above and below the dotted line gives you a tiny bit more information than you would otherwise have, and the result is both aesthetically pleasing and impressively lucid. Great work!

FYI, my index finger is indeed longer than my ring finger. Go figure.

Colorbar Confusion

A press release from Purdue University describes the effect of greenhouse gas emissions on “heat stress,” using the diagram above to illustrate the difference in effect between accelerated emissions (top) and decelerated emissions (bottom). A description from the web page:

“This image illustrates heat stress in the 21st century for two greenhouse gas emissions scenarios. The top panel shows the expected intensification of the severity of extreme hot days given accelerating increases in greenhouse gas concentrations. The bottom panel shows the expected decrease in intensification associated with decelerated increases in greenhouse gas concentrations.”

(I apologize for the nearly illegible size… The Purdue website offers up the diagram in the teeny-tiny size above, or print quality, which I assumed would be excessive.)

There are a couple of things I find odd (and counterintuitive and frankly counterproductive) about the diagram…

Firstly, the color spectrum used in this false-color representation of the data feels wrong to me, since it ranges from cool blues through warm oranges and reds and thence to… The beginnings of a cool violet? Particularly since we’re talking about temperature (well, sort of) here, and most people have grown accustomed to weather maps colored by temperature. Stopping at red gives you plenty of color resolution. (And maybe next time, you can choose something other than the garish rainbow colors?)

A more egregious error permeates the diagram, however. Perhaps we can simply call this the “apples and oranges&rduo; issue: two images, side-by-side, offered up for comparison, need to share enough to allow for easy comparison. I last blogged about this in relation to an NCAR visualization of Hurricane Katrina, but the idea is simple enough: don’t ask the viewer to do unnecessary work in interpreting your imagery, because unnecessary work leads to unnecessary risk of miscommunication. In the case of the two images above, the color bars are flipped for no apparent reason, so increasing values get warmer (in hue) on the top and cooler (in hue) on the bottom. Why? Also, the scale of the two color bars changes, running from 3 to 8 on top and from –3 to 0 on the bottom. Why? Why? Why?

(Well, okay, I can acknowledge one drawback in this particular case. Since the two datasets do not overlap, coming up with a single colorbar would be a little tricky; indeed, you’d almost need to insert an intermediate model showing, say, no change in greenhouse admissions, which would presumably result in values in between. But the issue of inverting the colorbar still stands: “red on top bad, red on bottom goooood” simply leads to confusion.)

I find behavior of this sort annoying when watching a scientist presenting data in a talk, but as part of a press release, it just saddens me. My fear is that the folks in the university press offices don’t even try to fix these problems… Perhaps because they don’t care, but perhaps because they don’t even think the data should be easily understood.

Hmmm. Maybe it’s time for a Tufte-like “Graphics 101” for science types? I looked for such a thing just now, but I didn’t find anything. Anyone reading know of such a thing?