I recently came across this awesome optical illusion, first described by Stuart Anstis. Two bars, one red and one blue, move horizontally across the display. If a specific type of background texture is present, the two rectangles appear to move in anti-phase: When the red rectangle moves quickly, the blue one grinds to a halt, and vice versa. This is illusionary, of course, and the effect is gone when the background texture is removed.

The two rectangles resemble a pair of stepping (or shuffling) feet, hence the name: the stepping feet illusion. (The effect is strongest for some people if you don't look directly at the rectangles.)

The explanation for this illusion appears to be fairly straightforward (but see [1]). And, as any good illusion, it provides some insight into how our visual system works.

The crux is that the illusion will not work with just any pair of colours: There must be a luminance difference. Put differently, one stimulus must be bright (the blue rectangle in this case) and the other must be dark (the red one). In addition, there must be a comparable luminance difference in the background, which is achieved here through a pattern of alternating light and dark bands.

Now, let's say that the front and hind edges of the stimuli are on a dark band, as in a) in the figure below. In this situation, there is little contrast between the side edges of the red stimulus and the background (both are dark). Because of …

Oxford University Press, 2011 (Paperback)

Conclusion From turbulent rivers to auto-catalytic chemical reactions. With the "Nature's Patterns" trilogy, Philip Ball gives us an eclectic, yet surprisingly coherent overview of all kinds of patterns that are found in nature. It's an interesting and challenging read, but perhaps a single book would have sufficed.

Why are honeycomb cells hexagonal? Why do spotted animals tend to have striped tails? And, for that matter, why are animal pelts so often spotted or striped, rather than endowed with, say, a rectangular grid? Why does Jupiter have a giant red spot?

The diversity of the issues that Philip Ball takes on in his trilogy on nature's patterns is overwhelming. Most of them cannot even be said to have much in common: Jupiter's red spot cannot be explained in the same way as the shape of a honeycomb cell. Yet, despite his eclectic subject matter, Philip Ball manages to tell a coherent story. One that goes far beyond stamp collecting of interesting factoids.

A recurring theme in the three books (Shapes, Flow, and Branches) that together form Nature's Patterns: A Tapestry in Three Parts is that many patterns are 'emergent properties'. Spotted and striped pelts do not necessarily provide the best possible camouflage, so they cannot be fully explained in Darwinian terms. Nor is it practical (even if perhaps theoretically possible) to explain such patterns in terms of the laws of physics. Instead, Ball argues, to explain why spots and stripes are so common, you need to …

When writing a scientific paper it is considered good style to convey an absolute and unrelenting trust in your own findings. So in many papers the discussion section starts with something like 'the present study is the first to conclusively show that (...)' or 'the results clearly show that (...)'.

I've written a few lines like that as well. But, tainted with hypocrisy, I actually find this style of writing a bit weird. It is no secret that cognitive science is a messy business, and that experimental data is seldom clear-cut. Most scientists, and certainly the good ones, are quite frank about this. So why the sudden attack of confidence when writing a paper?

Well... I don't know, and perhaps it is just a matter of style without any real reason. Fashion, in a sense. But it does strike me that this is a relatively new phenomenon, and that scientists in the past were much more equivocal in their writing. The quite recent past, even. Take, for example, Michael Posner, who wrote in the abstract of his seminal 1980 paper Orienting of Attention that '(...) the possibility is explored that (...)'. Or Giacomo Rizzolatti, of mirror neuron fame, who wrote back in 1987 that '(...) the hypothesis is proposed that postulates (...)'. Both of these sentences (which were of course cherry-picked for the occasion) convey a modest degree of belief in ones own theory and/ or findings: I believe in X, but I could be wrong.

I thought it would be cool to analyse the PubMed …

PubMed is a popular search engine for biomedical literature. It has lost a lot of ground to Google Scholar over the past few years, but for a long time it was the go-to scientific search engine for psychologists, neuroscientists, and the likes. And the cool thing is that, unlike Google Scholar, PubMed allows you to write scripts to automatically download enormous amounts of information.

Which is what I did over the weekend: I downloaded information about scientific articles. Names, authors, abstracts (summaries), journal titles, etc. And lots of it. I figured I would eventually get banned for abusing the PubMed service, but I didn't, and the end result is a database containing 257.535 articles published between 1950 and 2010 in 43 academic journals, broadly focused on neuroscience and cognitive psychology [1]. To the extent that PubMed has a complete index, this should include a large proportion of all articles published between those years in those journals.

So that's a lot of data!

I'm planning to write a series of blog posts, each time focusing on a different aspect of this data set. My main aim will be to understand the whole system academic publishing just a little bit better, and to see how it has evolved over the years. All the while keeping in mind, of course, that even these quarter of a million articles reflect just a tiny fraction of the total volume of scientific output. And a biased fraction at that, because the journals have been hand-picked …

I recently stumbled across a great video tutorial for the OpenSesame experiment builder. This video, created by Chris Longmore, shows how to build an experiment in which participants have to judge the gender of a (picture of a) cat. This is kind of goofy, but experiments of this kind have been conducted at least twice. Once by Quinn and colleagues, and once by Longmore himself. And, apparently, people are able to distinguish male cats from female cats. Barely, but still. (You can participate in an online version of the experiment here.)

Here's the video:

And, because I'm sure you're wondering, here are some pictures of cats split by their actual and perceived gender. It seems (to me) that people go largely by colour and size: Big, dark cats look male, whereas slender and lightly coloured cats are perceived as females.

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