A few days ago, Kubuntu 13.04 Raring Ringtail was released. I am a Kubuntu user myself, and to celebrate this new release, I wanted to share a few tips on how to set up the perfect Kubuntu environment for neuroscientists and psychologists. Of course, the ‘perfect’ environment is different everyone, but there are a few things that almost every researcher in this field will need: An office suite, a reference manager, graphics software, statistics and analysis software, and experiment building software.

What is Kubuntu?

Kubuntu is a Linux distribution. If you’re not familiar with Linux, this may not mean much to you, so let’s start with a little background.

Some relations between various flavors of Linux.

A Linux-based operating system is a layer cake. It consists of many layers of software that can be stacked and combined in an infinite number of ways. Only the bottom layer is constant: That’s the Linux kernel, which is part of all Linux-based operating systems, including Android. On top of the kernel, there can be different layers of software. Kubuntu is essentially one specific selection of software. Other Linux distributions, such as openSUSE, have slightly different selections. Some differences are clearly visible, such as different desktop environments (i.e. the software that controls the start menu, etc.). Other differences are largely under the hood, such as different system management tools.

A Linux distribution arranges the many layers of software in such a way that you, as a user, don’t …

Let’s consider a biologist with an interest in swan coloration. She goes on an expedition to an area where two groups of swans live, to investigate whether the two groups have different colors. The biologist takes her job very seriously, and first calibrates a photometer against two reference colors: One for the ideal black swan; one for the ideal white swan. She then measures the color (or rather luminance) of ten specimens from each group, obtaining a range of values where 0 is ideal black and 100 is ideal white:

To analyze her results, she runs an independent samples t-test on the measurements, which tells her that p = .0001. This leads her to conclude that the two groups have different colors. Just as she suspected all along:

Our biologist is probably satisfied at this point. But we are not. What exactly has she learned from this t-test and the resulting p-value? Let’s start with the basics: What exactly does p = .0001 mean? Well … it means that if the two groups were really of the same color, the chance of observing a color difference as extreme as she observed, or more extreme, is .0001. This is an odd and counter-intuitive statement. Yet it is the foundation of most research.

Personally, I have a hard time understanding statistics, and null hypothesis testing (the type of statistics that gives you p-values) in particular. And I when I finally think I have some grasp on it, the paradoxes …

I’m typing this blog on a Raspberry Pi, a £25 / €30 / $40 mini computer that is literally the size of a credit card.

The Pi is an adorable machine (if you’re into that kind of stuff): Just a small printboard with connectors for a monitor, mouse, keyboard, and an ethernet cable. The system boots from an SD card, so there is no hard disk. There is a choice of Linux-based operating systems, the most commonly used being Raspbian, a Debian spin-off that has been optimized for the Pi. This is also what I installed. And in case you’re wondering: I didn’t open the Pi up – It just doesn’t come with a casing!

Because the Pi is extremely cheap, some people have wondered whether it could be used to equip low-budget psychology labs. This is also how I came into the possession of this diminutive cutie: It’s a gift from Clayton, who wondered how well OpenSesame would fare on the Pi. Thanks Clayton!

If you promise to keep reading, I’ll give you the answer now: Moderately well, with a few caveats.

Snappiness, OpenGL, and v-sync

The operating system on the Pi does not support OpenGL, which is the library used for hardware-accelerated graphics by OpenSesame (or actually by Expyriment and PsychoPy, which are used by OpenSesame). This is a shame, because the Pi comes with a decent graphics unit, which is now essentially unused. However, OpenSesame’s non-hardware-accelerated back-end (legacy, which is PyGame based …

Based on (critical) responses that I received, and discussions that I had after this post, I have added some footnotes to elaborate on certain aspects. The main criticisms are that pre-registration is not necessarily as rigid as I depict it to be (which may be true), and that questioning statistical guidelines is dangerous (which is certainly true, but also a moralistic fallacy: something can be correct and dangerous to say at the same time). Also, see my (sort of) follow-up post The Black Swan and NeuroSkeptic’s response.

In response to the many recent cases of scientific fraud, a debate has ignited about how science can be made more transparent, and how some of the public trust can be regained. Suggestions include …

An evil scientist.

• making all research data publicly available, not just the summarized results.
• making all scientific papers publicly available (i.e. open access).
• investing more time in replicating results, those of others as well as your own (e.g., the reproducibility project).
• and pre-registering all studies.

A slightly mysterious, but influential voice in this debate is Neuroskeptic. In a recent post, Neuroskeptic interviews Jona Sassenhagen, a neurolinguist from the University of Marburg, who decided to pre-register his EEG study. So what does it mean to pre-register a study, and why would anyone do this?

The idea behind pre-registration is simple: Before you conduct your experiment, you publicly list exactly what kind of experiment you are going to conduct, how many participants you will test, and what the …

In the video below, you see Pac-man being chased by a ghost (again)¹. In the first part of the video, the maze scrolls so that Pac-man stays in the center of the screen (side-scroller perspective). In the second part, the maze stays put and Pac-man moves around (static perspective). Both perspectives are used in video games. The side-scroller perspective is used in many older platform games, such as Super Mario Bros, and is in many respects similar to the first-person perspective used in most action games today. The static perspective is used mostly in simple games and very old games, such as Snake and the original Pac-man.

So both perspectives offer perfectly acceptable gameplay. But the difference in your ability to detect changes is dramatic!

With the static perspective, you can see quite clearly that the maze is changing all the time: Except for a few tiles around Pac-man, the whole maze is randomly re-generated with each frame. However, with the side-scroller perspective these changes are much less noticeable, to the point that you may have failed to notice them at all, at least for a while.

So why does the perspective make such a big difference?

You might think that with the side-scroller perspective, there is already quite a lot of change going on, because the maze slides across the screen. The changing structure might simply get lost in the chaos. In contrast, with the static perspective, the maze structure is the only thing that changes, and is …