Recently, Sebastiaan managed to port the OpenSesame experiment builder to the Android operating system. Since then, I've spent some time working on adapting OpenSesame so that it can be used to create and package experiments that participants can download from the Google Play Store like any other app. When the participant has finished an experiment on his/her tablet or phone, the data are automatically sent back to the experimenter over the internet.

So far, I have designed and uploaded a simple reaction time experiment to test this idea, which I would be grateful if you could take a few minutes to download and try.

The app consists of a few questions about the phone you are using, a prototype of a new on-screen keyboard feature, and 32 trials of a basic reaction time task. If, for whatever reason, the app doesn't work as expected on your phone or tablet, please leave a comment below or on the forum.

The Smartphone Revolution

The spread of smartphones over the last few years has been phenomenal, and for the first time a huge proportion of the young adult population (who psychologists have traditionally relied upon as subjects anyway) carry powerful computers with touchscreen interfaces with them wherever they go.

Smartphones also offer a number of features not seen in the average lab computer, including an accelerometer, one or more cameras, vibration feedback, and in the future even eye-tracking technology. The potential of smartphones to revolutionise behavioural research is discussed in this review …

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.

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 …