Monthly Archives: October 2013

High-tech version of the hollow-face illusion

I just accidentally made a kind-of version of the classic hollow-face illusion, using an anatomical MRI scan of my own head and Osirix. I exported a movie in Osirix, saved the movie as an image sequence using Quicktime, and then assembled it into an animated GIF using GIMP.

MW_3D_MIP_2 001_small

Click the image for a much bigger (11mb!) version.

This is a maximum intensity projection, and because of the way MIPs work, it appears that the head is rotating 180 degrees to the left, and then the direction switches and it rotates back 180 degrees to the right. In actual fact, the image is rotating constantly in one direction, as can be seen by looking at the cube on the top left which cycles through L (Left), P (Posterior), R (Right), and A (Anterior). It’s not really a hollow-face illusion as the effect is pretty much an artefact of the MIP, but still, I thought it was cool.

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This page on how to design and make scientific conference posters…

…is really, really brilliant, and you should all go and look at it. That is all.

LINK

Some Python resources

videosong

Since I’ve switched to using PsychoPy for programming my behavioural and fMRI experiments (and if you spend time coding experiments, I strongly suggest you check it out too, it’s brilliant) I’ve been slowly getting up to speed with the Python programming language and syntax. Even though the PsychoPy GUI ‘Builder’ interface is very powerful and user-friendly, one inevitably needs to start learning to use a bit of code in order to get the best out of the system.

Before, when people occasionally asked me questions like “What programming language should I learn?” I used to give a somewhat vague answer, and say that it depended largely on what exactly they wanted to achieve. Nowadays, I’m happy to recommend that people learn Python, for practically any purpose. There are an incredible number of libraries available that enable you to do almost anything with it, and it’s flexible and powerful enough to fit a wide variety of use cases. Many people are now using it as a free alternative to Matlab, and even using it for ‘standard’ statistical analyses too. The syntax is incredibly straight-forward and sensible; even if an individual then goes on to use a different language, I think Python is a great place to start with programming for a novice. Python seems to have been rapidly adopted by scientists, and there are some terrific resources out there for learning Python in general, and its scientific applications in particular.

For those getting started there are a number of good introductory resources. This ‘Crash Course in Python for Scientists’ is a great and fairly brief introduction which starts from first principles and doesn’t assume any prior knowledge. ‘A Non-Programmers Tutorial for Python 2.6′ is similarly introductory, but covers a bit more material. ‘Learn Python the Hard Way’ is also a well-regarded introductory course which is free to view online, but has a paid option ($29.95) which gives you access to additional PDFs and video material. The ‘official’ Python documentation is also pretty useful, and very comprehensive, and starts off at a basic level. Yet another good option is Google’s Python Classes.

For those who prefer a more interactive experience, CodeAcademy has a fantastic set of interactive tutorials which guide you through from the complete beginning, up to fairly advanced topics. PythonMonk and TryPython.org also have similar systems, and all three are completely free to access – well worth checking out.

For Neuroimagers, there are some interesting Python tools out there, or currently under development. The NIPY (Neuroimaging in Python) community site is well worth a browse. Most interestingly (to me, anyway) is the nipype package, which is a tool that provides a standard interface and workflow for several fMRI analysis packages (FSL, SPM and FreeSurfer) and facilitates interaction between them – very cool. fMRI people might also be very interested in the PyMVPA project which has implemented various Multivariate Pattern Analysis algorithms.

People who want to do some 3D programming for game-like interfaces or experimental tasks will also want to check out VPython (“3D Programming for ordinary mortals”!).

Finally, those readers who are invested in the Apple ecosystem and own an iPhone/iPad will definitely want to check out Pythonista – a full featured development environment for iOS, with a lot of cool features, including exporting directly to XCode (thanks to @aechase for pointing this one out on Twitter). There looks to be a similar app called QPython for Android, though it’s probably not as full-featured; if you’re an Android user, you’re probably fairly used to dealing with that kind of disappointment though. ;o)

Anything I’ve missed? Let me know in the comments and I’ll update the post.

Toodles.